power bi assignments for practice

15 Power BI Projects Examples and Ideas for Practice

Master Power BI Skills By Gaining Hands-on Experience on These Amazing Power BI Projects in 2022 | ProjectPro

Preparing for your next BI developer interview? Check out these Power BI projects that will blow your mind with Power BI’s interactive dashboards, exceptional graphs and charts, and many more features.

We will look at some intriguing sample Power BI projects in this blog to help you better understand the role of Power BI in Data Science and how it can help businesses thrive.

Table of Contents

What is power bi, what is power bi used for, how to do visualization in a power bi project, 15 power bi project examples , 1. customer churn analysis, 2. product sales data analysis, 3. marketing campaign insights analysis, 4. financial performance analysis, 5. healthcare sales analysis, 6. anomaly detection in credit card transactions , 7. automl cashflow optimization for insurance company , 8. global health expenditure analysis, 9. loan application analysis, 10. movie sales visualization, 11. airport authority data analysis, 12. covid-19 insights analysis , 13. construction permit data analysis, 14. global energy trade analysis, 15. life expectancy data analysis, 16. twitter analysis dashboard, 17. ott media dashboard, 18. adventureworks database analysis, retail analysis power bi report example, global covid-19 analysis power bi report example, inventory stock analysis power bi report example, cancer analytics power bi report example, customer analysis power bi report example, master data visualization with these power bi projects.

• What projects can I do with Power BI?
• How do you practice Power BI?
• Where can I get practice data for Power BI?

Microsoft Power BI is a Business Intelligence service that enables you to create visually rich and interactive dashboards and reports based on the raw business data acquired from various sources. Apart from the variety of apps, connectors, and services offered by Power BI, there are three basic elements integrated into Power BI- 

Power BI Desktop (a desktop version),

Power BI Service (an online SaaS service), and

Power BI Mobile Applications for several platforms.

Business users utilize these services to collect data and generate BI reports. These three components are all meant to assist in building, exchanging, and leveraging business insights in the most efficient way possible for any business. Some of the benefits of leveraging Power BI include-

Easy Interaction with Existing Applications: Power BI makes it far easier to implement analytics and reporting abilities since it seamlessly connects with your current business environment.

Customized Dashboards: The information dashboard can be tailored to meet the demands of a company. The application can simply include Power BI dashboards and reports to create a smooth user experience.

Advanced Analytics with R Integration: R programming language has several packages focusing on data mining and visualization. Data scientists employ R programming language for machine learning, statistical analysis, and complex data modeling . Data models created in R may be easily integrated into Power BI dashboards and turned into visualizations.

No Storage or Performance Limits: There are no memory or speed constraints when migrating an existing BI system to a robust cloud environment with Power BI integrated, ensuring that data can be fetched and analyzed efficiently.

Securely published reports: Power BI enables automatic data refresh and publishes reports securely, allowing users to access the most up-to-date data.

New Projects

There are various tools and techniques for analytics and machine learning in the fascinating and extensive realm of data science. Power BI is a high-level, all-in-one solution for data analytics in data science. Data science aids in the discovery of relevant and productive trends and insights. It involves analyzing the data and also assists us in identifying entirely new features in it. Business intelligence is sifting through data to extract meaningful organizational ideas and insights. BI enhances and strengthens the business infrastructure to get desired or projected results.

Many data sciences and analysis tasks can be automated with Power BI, eliminating the need for spreadsheets and static presentation tools. One of Power-most BI's most impressive features is its ability to create stunning visualizations. The software is packed with excellent and eye-catching visualization templates. The integration of Power BI into Data Science holds great importance for businesses. This allows for smooth and effective data visualization, which plays a vital role in an organization’s success. 

With the help of Power BI, visualization in Data Science can be taken a notch further. Businesses and Data Scientists rely heavily on Power BI-aided data visualization for various projects. Numerous visualization types and charts are available in Power BI for creating effective visualization for data science projects .

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There are two ways to generate visualization in Power BI. First, add items to Report Canvas from the right side pane. Another way you can do this is by dragging the fields from the right sidebar to the value axis under Visualization. By default, Power BI selects the table type visualization. To each axis, you can add as many fields as necessary. You can also click and drag your visualization to rearrange it on the reporting panel. You can easily toggle between various charts and visualizations from the Visualization window. Your specified fields are transformed to the new visual format as accurately as possible.

Let us now understand how one can perform data visualization in Power BI.

The first thing you need is data. Power BI can connect several data sources- Excel, Web, etc. The options from which data can be imported into the Power BI desktop are all visible once you click the Get Data icon. You can view the data in the Fields pane once it has been loaded.

After loading the sample data into the Power BI desktop, you can modify it with the help of Query Editor. Regardless of the data source, query editors are helpful for editing datasets . In the query editor, you can perform changes like renaming a dataset and removing one or more columns, among other things.

In Power BI, removing columns from the dataset or modifying the data types in the columns is relatively easy. You can remove columns by simply choosing the Remove Columns option after selecting the desired column. Likewise, the query editor makes it simple to perform a wide range of actions like removing and adding rows, transposing, pivoting, and splitting.

Once the dataset is complete and has undergone all necessary modifications, you can move on to creating the dashboard. Both bubble and shape maps are available for map visualizations in Power BI. To plot measure values, Power BI offers several combination chart types. Suppose you want to display overall sales and revenue on the same chart. The ideal option for this type of scenario is combination charts.

You can change the colors in the charts in BI dashboards. There is a color selection option when you choose any visualization.

Additionally, the application has an analytics feature that allows you to draw lines for data visualization according to your preferences. Power BI also has the option to add various shapes, texts, and images when visualizing data.

This blog lists 15 Microsoft Power BI projects for you. We have categorized these Power BI examples into beginner, intermediate, and advanced levels. You can choose any of these power bi projects for practice to upskill yourself in the Data Science domain. 

Beginner-Level Power BI Project Basic Examples

In this section, we have included some Power BI projects for students. These simple Power BI projects will enable you to understand business intelligence applications and build a successful career as a data scientist.

The customer churn analysis project is one of the easiest and most popular Power BI sample projects. Customer Churn Analysis reveals regional customers' product sales and profits. Analytical users can use it to analyze regional business growth across geographies to gain valuable insights and distribute profits among customers. They can receive extensive data by using the right visualizations and data structure. The project includes regional cash inflows and product-specific customer churn over time.

For this beginner-friendly project, use the customer segmentation dataset available on Kaggle. In the analysis overview page, you could use Combo Charts, Cards, Bar Charts, Tables, or Line Charts; for the customer segmentation page, you could employ Column Charts, Bubble Charts, Point Maps, Tables, etc.

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Businesses must keep detailed records of their sales for a variety of reasons. However, if there is too much data, it often becomes difficult to keep track of everything. Analyzing sales data allows companies to keep track of their sales and answer all critical questions regarding their performance.

This sales data analysis project entails analyzing a company's sales data and indicating profit by product, sales, and other significant factors that might influence the company's performance. You can use Microsoft's sample dataset . The data set must be connected to Power BI Desktop to remove irrelevant data before visualizing and exporting the filtered data as dashboards. The dashboard could leverage Power BI visualization types such as Pie Charts, Bar Charts, Doughnut Charts, Funnel Charts, etc.

The project idea is to showcase the efficacy of various marketing campaigns and the performance of product groups and platforms using any marketing analytics dataset. This project is an excellent approach for a marketing manager to assess the success of marketing campaigns.

Use the Marketing Analytics dataset available on Kaggle for this beginner-level project. For the data visualization dashboard, you can explore many of the Power BI visualization types, such as Bar Charts for category-wise expenditures, Column Charts for campaign success rate, Smart Narratives for displaying the key highlights of the campaign, Bubble Charts for customer-wise spending, Cards for showing individual data insights, etc.

Financial performance analysis is one of the most intriguing Power BI project ideas for beginners. This business intelligence project approach is based on optimizing financial analysis for a firm that provides accounting services to clients who seek timely delivery of critical financial reports. You can set up the analysis to quickly access reliable financial data. The project might be used to: migrate traditional financial reporting from Excel to current BI dashboards and provide customers with an effective tool to track their financial health and productivity.

Refer to the multi-company financial dataset available on Kaggle. You can leverage Power BI data visualization in this project for three different cases-

- for the summary/overview page, you can use Funnel Charts, Combo Charts (Column Charts, Line Charts, Waterfall Charts); 

-for the income statement page, you can use Cards, Funnel Charts, and Combo Charts (Line Charts and Column Charts); and

- for the balance sheet page, you can use Cards and Tables.

This business intelligence project idea enables those in the Animal Healthcare sector to efficiently track the sale of products dedicated to treating minor animal species. Businesses may instantly compare product sales in top-ranking and bottom-ranking cities. The project could generate a thorough report on therapeutic group-wise sales and the sales trends for any specified period.

You can refer to the pharma sales dataset available on Kaggle. For the data visualization on Power BI, you might use Tables for displaying the therapeutic group-wise sales, Column Charts for monthly sales trends; Bar charts for top and bottom-ranking cities; and also, you can include Treemaps, Cards, Smart Narratives, etc. You can also check out the Microsoft Power BI community for some beginner-friendly power bi project examples.

Learn more about Big Data Tools and Technologies with Innovative and Exciting Big Data Projects Examples.

Intermediate-Level Power BI Project Ideas

If you’re already well-versed with the Power BI data visualization tool and are willing to strengthen your data analytics skills further as a Data Scientist, here are some power bi projects for resume-

The first Power BI project idea we have come up with is Anomaly Detection in Credit Card Transactions. Anomaly Detection is a machine learning technique for detecting unusual things, events, or observations that differ considerably from the rest of the data and look suspicious. You can implement this machine learning method in three ways- supervised (for labeled datasets), semi-supervised (for normally trained datasets), and unsupervised (for datasets without any labels).

For this project, you can use the credit card dataset by Delaware available on their open data platform itself or the credit card fraud detection dataset from Kaggle. You must first import the dataset into the Power BI desktop, maybe via a web connector. You can then leverage Power BI to train your anomaly detector or use a pre-trained model. To label outliers in Power BI, you'll need to run a Python script in the Power Query Editor and use the get_outliers() method. Finally, Power BI Dashboard can be used to visualize it. You could also train your anomaly detection model in any IDE or Notebook and then pass it to Power BI for labeling. You can do the data visualization in the Power BI dashboard with the help of Line Charts, Bubble Charts, TreeMaps, etc.

Automated machine learning (AutoML) is the technique of automating machine learning's time-consuming, iterative processes. It enables data scientists and analysts to rapidly create machine learning models while retaining model quality. Any AutoML solution's ultimate goal is to identify the optimal model based on performance metrics.

In this business intelligence project, you can work with the medical cost personal dataset from Kaggle. The business problem involves an insurance company that wishes to improve its cash flow projections by precisely estimating patient charges through demographic and primary patient health risk variables at the time of hospitalization. The first step is accessing Power BI Desktop, loading the dataset, and replicating it. The Python script may then be executed in Power Query, where the compare_models() method can be used to train different models, compare them, and evaluate their performance data. You may also use the automl() function to find the best-performing model out of all of them. For the resulting dashboard, you can leverage Power BI dashboard features such as Bar Charts, Bubble Charts, Tables, etc.

One of the most helpful Power BI project ideas is the Global Health Expenditure Analysis. This project idea is based on implementing clustering analysis in Power BI using PyCaret. Clustering is a method for bringing data items together that have similar features. These classifications help study a dataset, detect patterns, analyze data, and data clustering help in identifying underlying data structures.

In this case, use the current health expenditure dataset from the WHO Global Health Expenditure database. From 2000 to 2018, the dataset includes health expenditure as a percentage of national GDP for over 200 nations. Also, you could use the K-Means clustering algorithm for the clustering analysis. Visualize the cluster labels in Power BI Dashboard to gain insights after you have loaded the dataset in Power BI Desktop and trained your clustering model in Power BI. For the summary page dashboard, you might choose visualization chart types such as Filled Maps, Bar Charts, etc., while for the detailed visualization, you can use Point Maps.

This project concept entails evaluating loan application data to find abstract 'topics,' which are then used to assess the impact of specific topics (loan types) on the default rate. It is based on implementing the Latent Dirichlet Allocation (LDA) topic model in Power BI. Topic modeling aims to automatically analyze a collection of documents and determine their abstract ‘topics’.

For this project, you can use the Kiva dataset on GitHub, which covers loan data for 6,818 accepted potential borrowers. The loan amount, nationality, gender, and some text data from the borrower's application are included in the dataset. Once you have loaded the dataset in Power Bi desktop, trained your model, and the topic weights are added to the original dataset in Power BI, you can visualize it in the Power BI dashboard by employing the Word Cloud feature, Pie Charts on basic maps, Bar Charts, Scatter Charts, etc.

The movie sales visualization project is one of the most exciting Power BI project ideas. This project aims to take a dataset that shows movie sales over time and turn it into an interactive visual experience. You can use the IMDb dataset for 2006 to 2016, available on both IMDb and Kaggle. The dataset includes a list of movies having an IMDb score of 6 or higher and the parameters Budget, Gross, Genre, and Scores. 

You can create a custom Radial Bar Chart and use Slicers to pick Genre, Country, and score range to be integrated directly into PowerBI. This would display parameters such as Average Score and Gross Collections for the selected set. Plotting a Histogram on the score variable using year and genre as slicers will show the frequency distribution of the IMDb scores. A KDE plot can provide a density graph and insights into the average rating for a specific genre and distribution for a given timeframe.

Advanced-Level Power BI Project Ideas

Lastly, we have listed some of the best power bi projects for professionals who need some interesting power BI projects with dataset to try their hands on. 

The Airport Authority Data Analysis project aims to provide a clear picture of all the significant airport data. The total number of flights (incoming and departing flights), the total number of flight delays (arrivals and departures), ground processing time, and the passenger feedback section can all be included in the summary page of this project’s dashboard. In case of flight changes, emergencies, or delays, this analysis could assist airport management authorities in making timely data-driven choices.

For this project idea, you can use the Airline delays and cancellation dataset available on Kaggle. The dataset includes multi-year airline data from 2009 to 2018 to provide more time-series insights. For flight analysis, you can use Power BI visualization options like Cards, Bar Charts, Flow Maps, TreeMaps, and Tornado Charts. For passenger feedback, you might prefer to use Bar Charts, Column Charts, or Cards.

Covid-19 Insights Analysis is one of the most popular Power BI project ideas among individuals. The project aims to thoroughly overview the Covid-19 pandemic's essential parameters, the latest situation, and detailed country-level evaluations. You can create a dashboard that gives valuable information regarding cases (active, deceased, or recovered), mortality, and recovery rates by nation and timeframe. Also, the dashboard might even include a management summary of the most important KPIs and a thorough analysis of individual report pages.

Refer to the Covid-19 dataset available on Kaggle for this project idea. As for the Power BI data visualization features, you can use- Bar Charts, Point Maps, Line Charts, and Column Charts for the overview page; Doughnut Charts for category-wise case analysis; and Decomposition Trees for country-wise case analysis. You might also use Heat Maps to enhance your project’s dashboard visualization.

Explore Categories

The project idea is to help construction firms better understand the industry by allowing them to dig deeper into the specifics and research relevant incidents. You can focus your project on details such as investment growth over time, investment concentrations in specific areas if the investment is impacted by Category, Contractor, or Individual, market status, and which categories, individuals, and permits are driving the market.

For this project idea, use the Seattle building permits dataset from Kaggle. You can perform  Power BI data visualization with the help of Regional Maps, Pie Charts, Bar Charts, Tables, Cards for the main page, Bar Charts, and Line Charts for depicting contractor competitions and category-wise growth, etc.

One of the most unique power bi projects ideas is the Global Energy Trade Analysis. This project concept includes various topics concerning global energy exchange and production. It addresses several topics, such as the expansion of wind energy, energy consumption as a different basis for comparing national economies, etc.

For this unique project idea, use the international energy statistics dataset from Kaggle. The resulting dashboard could display total energy statistics on production, exchange, and usage of primary and secondary energy, conventional and non-conventional energy sources, and new and renewable energy sources. For the dashboard, you can use Power BI visualization types such as Bar Charts, Flow Maps, Cards for the overview page, Ribbon Charts, Treemaps, Bar Charts for the energy production and exchange pages, etc.

This project will analyze life expectancy data by looking at factors such as immunizations, mortality, finances , social factors, and other health-related issues. It will make it easier for a country to identify the predicting factor contributing to a lower life expectancy value. This will also aid in recommending to a country which areas should be prioritized to effectively raise the population's life expectancy.

Use the life expectancy dataset by WHO on Kaggle for Life Expectancy Data Analysis. Power BI visualization types such as Gauge Charts, Pie Charts, Line Charts, and Point Maps can be used for the overview page, while Tornado Charts, Doughnut Charts, Treemaps can be used for depicting country-wise data, etc.

Power BI Projects Github

Here are a few unique project ideas from GitHub that will help you better understand the various applications of Power BI.

This project entails implementing an end-to-end Twitter data analysis/ETL pipeline. For this Power Bi project idea, use the Twitter data from Github . After extracting the data, you will transform it from JSON to CSV and create all the necessary derived attributes. You will then use NLP analysis to classify the tweets' content and determine their sentiment score. Once you finish the ETL process, you can move on to visualize your data using Power Bi reports. For creating the dashboard, you will use pie charts, bar graphs, line charts, tree maps, doughnut Charts, etc.

This unique Power BI project entails visualizing various information related to multiple OTT platforms such as Netflix, Hotstar, Amazon Prime, etc. You can access this project's entire OTT media platform dataset from Github. Use the Query Editor in Power BI for data cleaning and preparation. Once your data is ready for visualization, you can display the visuals using various plots, graphs, cards, etc.

Suppose you have learned all the basics of Spark. What’s next? Start exploring ProjectPro’s repository, where you will find different Spark Projects for Practice.

You can work with the AdventureWorks data available on GitHub for analysis & visualization. Perform the query editing in Microsoft SQL Server Management Studio and use Power BI for the visualization part. Also, use MS Excel and Power BI's query editor for analysis.

Power BI Report Examples

Below are a few interesting Power Bi report examples to help you understand the power of data visualization using Power BI.

The retail analysis report presents a dashboard that analyzes product sales data from various retailers across various regions. The metrics include new-store analysis and a comparison of this year's performance to last year's in terms of sales, units, gross margin, and variation.

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With interactive visualizations based on readily accessible data, the Global Covid-19 Analysis Report contributes to fully disclosing COVID-19 trends worldwide. The report includes maps showing Vaccinations, Progress to Zero, Rt, Spread Analysis, Testing, and Risk Levels.

The inventory stock analysis report contains additional details on stock inventory and represents an analysis of stock inventory for 2018. Using this dashboard, you can forecast "Availability of Stock" and "Time to Replenish Stock" using information from the fulfillment cycle and markdown variance.

The Cancer Analytics report offers a brief overview and a thorough analysis of cancer patients in the US. It enables you to evaluate the mortality rates of each type of cancer, divided according to several factors. You can use the Cancer Analytics Dashboard to make well-informed decisions about the growing number of cancer patients in America.

The Customer Analysis Report highlights product sales and profit for local customers. It can be helpful for analytical users to gain valuable information on customer profit distribution and business growth across areas. The main highlights of the Customer Analysis report dashboard are the region-specific cash inflow and the clients' product-specific turnover.

These real-time power bi projects will help beginners and professionals upskill and master the ability to integrate business intelligence into Data Science. By working on these project ideas, you will gain a deeper understanding of leveraging Power BI for a data-driven approach to various data science industries and becoming job-ready. In case you are looking for some free Power BI projects for practice with solutions, you can head to open-source platforms like GitHub or Kaggle . ProjectPro offers more than 250 end-to-end project solutions around Data Science and Big Data, including some interesting data visualizations. 

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FAQs on Power BI Projects

1. what projects can i do with power bi.

Some of the projects you can do with Power BI are

Energy Trade Analysis

Covid-19 Analysis

Customer Churn Analysis

Movie Sales Visualization

2. How do you practice Power BI?

You can practice Power Bi by working on some unique and easy real-time Power BI examples available on ProjectPro, Github, Kaggle, etc.

3. Where can I get practice data for Power BI?

You can get practice data for Power BI in the platform itself, as the Power BI service has pre-built samples available.

Sign in to the Power BI service.

Browse to the workspace where you want to install the sample, whether it is My Workspace or another.

Select ‘Get data’ in the bottom-left corner. Choose Samples from the Get Data page that appears.

About the Author

Daivi is a highly skilled Technical Content Analyst with over a year of experience at ProjectPro. She is passionate about exploring various technology domains and enjoys staying up-to-date with industry trends and developments. Daivi is known for her excellent research skills and ability to distill

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Get samples for Power BI

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Are you new to Power BI and want to try it out, but you don't have any data? Or maybe you'd like to see reports that illustrate some of the capabilities of Power BI. We've got you covered.

Power BI offers different kinds of samples for different purposes. There are built-in samples and apps in the Power BI service, .pbix files, Excel datasets, and SQL databases. Here's a collection of different samples:

• The Sales & Returns sample Power BI report ( .pbix file). You can view it in the Data Stories Gallery, open and explore it in Power BI Desktop, or upload it to the Power BI service.
• The Artificial Intelligence sample Power BI report. In the report, explore the Power BI artificial intelligence features such as key influencers, root-cause analysis in a decomposition tree, and anomaly detection. Select Learn in the Power BI service navigation pane to download a copy from the Learning Center .
• A sample template app . Download it from AppSource, also right in the Power BI service. Template apps include dashboards, reports, and semantic models. You can modify them, then distribute them to your colleagues.
• Eight original built-in samples in the Power BI service, with dashboards, reports, and semantic models. You install them right in the Power BI service. The built-in samples are also available as Power BI reports ( .pbix ) and Excel workbooks ( .xlsx ).
• Excel workbook versions of the built-in samples, containing the data model. Explore the data model in the Power Pivot add-in for Excel or use the Excel workbook as a data source for a Power BI report.
• A Financial data sample workbook , a simple flat table in an Excel file available for download. It contains anonymized data with fictitious products, with sales divided by segments and countries/regions. It makes a useful basic data source for a Power BI report.
• An Excel workbook version of the AdventureWorks dimensional model , in a tutorial to walk you through creating a Power BI report with the data.
• If you'd rather work with data in SQL databases, the SQL samples article features links to downloadable AdventureWorks and WorldWideImporters SQL databases in a GitHub repository. The article also has links to other Azure samples.

Our online documentation uses these same samples in tutorials and examples, so you can follow along.

Sales & Returns sample .pbix file

The following image shows the Sales & Returns sample report.

Power BI report designers Miguel Myers and Chris Hamill created the Sales & Returns .pbix file to demonstrate many new features in Power BI, including buttons, drillthrough, conditional formatting, what-if, and customized tooltips.

The scenario for this report is a company that sells Microsoft-themed skateboards. They want to see the state of their sales and returns, and analyze how they should modify their operations.

You can explore it these ways:

• Download the .pbix file and explore it in depth. Look "behind the curtain" to see how Miguel made it. This link opens the GitHub repo for Power BI Desktop samples . Select Download to download the Sales & Returns sample .pbix file to your computer.
• Read about the report in the Power BI blog post, Take a tour of the new Sales & Returns sample report .

Updated samples

There are revised versions of some of the original samples. These new versions take the original semantic models and incorporate the latest visualizations.

• Competitive Marketing Analysis. Take a tour of the Competitive Marketing Analysis sample.
• Corporate Spend. Take a tour of the Corporate Spend sample.
• Employee Hiring and History. Take a tour of the Employee Hiring and History sample.
• Revenue Opportunities. Take a tour of the Revenue Opportunities sample.
• Store Sales. Take a tour of the Store Sales sample.
• Regional Sales Sample. Take a tour of the Regional Sales Sample

To obtain these samples:

• Install the built-in samples in the Power BI service.
• Download the Power BI report files (.pbix) from the Power BI Samples GitHub repository.

Eight original samples

Eight original samples are available for you to use. Each sample represents a different industry. You can engage with each in different formats:

• Download the Power BI report files (.pbix).
• Download the Excel workbook files ( .xlsx ), then upload them to the Power BI service. Or explore the Excel files in Excel itself.

The company obviEnce ( www.obvience.com ) and Microsoft teamed up to create samples for you to use with Power BI. The samples use anonymized data. The samples represent different industries: finance, HR, sales, and more.

These samples are available in several formats: as a built-in sample, as an Excel workbook, and as a Power BI .pbix file. If you don't know what these things are, or how to get your hands on them, don't worry. This article explains it all.

For each of these samples, we've created a tour . Tours are articles that tell the story behind the sample and walk you through different scenarios. One scenario might be answering questions for your manager, another might be looking for competitive insights, or creating reports and dashboards to share, or explaining a business shift.

Before we get started, here are the legal guidelines for using these samples. After that, we introduce the samples and show how to use them.

Usage guidelines for the sample Excel workbooks

©2015 Microsoft Corporation. All rights reserved. The documents and workbooks are provided "as-is." Information and views expressed in the workbooks, including URL and other Internet Web site references, may change without notice. You bear the risk of using it. Some examples are for illustration only and are fictitious. No real association is intended or inferred. Microsoft makes no warranties, express or implied, with respect to the information provided here.

The workbooks do not provide you with any legal rights to any intellectual property in any Microsoft product. You may copy and use this workbook for your internal, reference purposes.

The workbooks and related data are provided by obviEnce. www.obvience.com

ObviEnce is an ISV and an Intellectual Property (IP) Incubator focused on Microsoft Business Intelligence. ObviEnce works closely with Microsoft to develop best practices and thought leadership for jump-starting and deploying Microsoft Business Intelligence solutions.

The workbooks and data are property of obviEnce, LLC, and have been shared solely for the purpose of demonstrating Power BI functionality with industry sample data.

Any uses of the workbooks and/or data must include the above attribution (that is also on the Info worksheet included with each workbook). The workbook and any visualizations must be accompanied by the following copyright notice: obviEnce ©.

By clicking any of the following links to download the Excel workbook files or .pbix files, you are agreeing to the terms above.

Customer Profitability sample

Take a tour of the Customer Profitability sample

This industry sample analyzes a CFO's key metrics for the company's executives, products, and customers. You can investigate what factors affect the company's profitability.

Human Resources / Employee Hiring and History sample

Take a tour of the updated Employee Hiring and History sample

This industry sample focuses on the hiring strategy for a company by analyzing new hires, active employees, and employees who have left. By exploring the data, you can find trends in voluntary separations and biases in the hiring strategy.

Take a tour of the previous version of the sample

IT Spend Analysis / Corporate Spend sample

Take a tour of the updated Corporate Spend sample

In this industry sample, analyze the planned versus actual costs of the IT department of a company. This comparison helps understand how well the company planned for the year and investigate areas with huge deviations from the plan. The company in this example goes through a yearly planning cycle, and then quarterly it produces a new Latest Estimate (LE) to help analyze changes in IT spend over the fiscal year.

Opportunity Analysis / Revenue Opportunities sample

Take a tour of the Revenue Opportunities sample

This industry sample explores a software company's sales channel. Sales managers monitor their direct and partner sales channels by tracking opportunities and revenue by region, deal size, and channel.

Procurement Analysis sample

Take a tour of the Procurement Analysis sample

This industry sample analyzes a manufacturing company's spending on vendors by category and location. You can investigate who the top vendors are, what categories the company spends the most on, and which vendors give the best discounts.

Regional Sales sample

Take a tour of the Regional Sales sample

This industry sample contains a report for a fictitious company named Contoso. The Contoso sales manager created this report to understand their products and regions' key contributors for revenue won or loss.

Retail Analysis / Store Sales sample

Take a tour of the Store Sales sample

This industry sample analyzes retail sales data of items sold across multiple stores and districts. The metrics compare this year's performance to last year's in these areas: sales, units, gross margin, variance, and new store analysis.

Sales and Marketing / Competitive Marketing Analysis sample

Take a tour of the updated Competitive Marketing Analysis sample

This industry sample analyzes a manufacturing company, VanArsdel Ltd. It allows the Chief Marketing Officer to watch the industry and the market share for VanArsdel. By exploring the sample, you can find the company's market share, product volume, sales, and sentiment.

Supplier Quality sample

Take a tour of the Supplier Quality sample

This industry sample focuses on one of the typical supply chain challenges: supplier quality analysis. Two primary metrics are at play in this analysis: total number of defects and the total downtime that these defects caused. This sample has two main objectives:

• Understand who the best and worst suppliers are, with respect to quality.
• Identify which plants do a better job finding and rejecting defects, to minimize downtime.

Install built-in samples

Let's start with the built-in samples . The built-in samples are available in the Power BI service. You don't have to leave Power BI to find them. These samples are each a bundle of one or more dashboards, semantic models, and reports that you can use with the Power BI service. These built-in samples aren't available for Power BI Desktop.

Open the Power BI service ( app.powerbi.com ) and sign in.

Select Learn in the left nav.

On the Learning center page, under Sample reports , scroll until you see a sample you want to open.

Select the sample. It opens in Reading mode.

Power BI imports the built-in sample. It adds a new report, and semantic model to My workspace . Some samples also include a dashboard. Use the samples to take Power BI for a test run.

Now that you have data, you're on your way. Try out some of our tutorials using the built-in samples or just open the Power BI service and explore.

Download updated sample .pbix Power BI files

The updated samples are also available as Power BI .pbix files. The .pbix files are designed to be used with Power BI Desktop.

Download the files individually using these links. Selecting these links saves the file automatically to your Downloads folder.

In Power BI Desktop, select File > Open , navigate to the location where you saved the sample .pbix file, and select the .pbix file to open it in Power BI Desktop.

Download original sample .pbix Power BI files

Several of the original built-in samples now have updated versions and these samples are available as .pbix files. Also, six of the original built-in samples are available as Power BI .pbix files. The .pbix files are designed to be used with Power BI Desktop.

Updated samples:

• Competitive Marketing Analysis
• Corporate Spend
• Employee Hiring and History
• Regional Sales Sample .pbix file
• Revenue Opportunities sample .pbix file
• Store Sales sample .pbix file

Original samples:

• Customer Profitability Sample PBIX
• Human Resources Sample PBIX
• Procurement Analysis Sample PBIX
• Retail Analysis Sample PBIX
• Sales and Marketing Sample PBIX
• Supplier Quality Analysis Sample PBIX

Download sample Excel files

Each of the built-in samples is also available as an Excel workbook. The Excel workbooks are designed to be used as a data source in the Power BI service or Power BI Desktop. If you're an advanced Excel user, you can explore or edit the data models in the Power Pivot add-in to Excel.

Download one or all of the sample Excel files from this GitHub repository.

• Customer Profitability Sample
• Human Resources Sample
• IT Spend Analysis Sample
• Opportunity Tracking Sample
• Procurement Analysis Sample
• Retail Analysis Sample
• Sales and Marketing Sample
• Supplier Quality Analysis Sample

Save the downloaded file. Where you save the file makes a difference.

You can use the files as data sources in Power BI Desktop , or Publish to Power BI from Excel to the Power BI service. When you publish, choose one of these options:

• Upload your workbook to Power BI : Brings the whole Excel file into Power BI.
• Export workbook data to Power BI : Creates a blank Power BI report with all your Excel data in the Fields list.

Explore Excel samples in Excel

Want to understand how the data in these Excel workbooks gets converted to Power BI semantic models and reports? Opening the Excel samples in Excel and exploring the worksheets provides some of the answers.

When you first open a sample workbook in Excel, you might see two warnings. The first warning says the workbook is in Protected View. Select Enable Editing . The second warning might say that the workbook has external data connections. Select Enable Content .

There's only one Excel sheet, the Info sheet. It provides information about obviEnce, the company that created the sample, and explains how to see the data in Power Pivot.

Where's the actual data? It's in the Power Pivot data model. On the PowerPivot tab, select Manage . In Power Pivot, you can see the data in all the underlying tables, plus all the DAX formulas.

Don't see the Power Pivot tab? Enable the Power Pivot add-in .

Upload the Excel files to the Power BI service

Navigate to your My workspace or to another workspace, or create a workspace just for the sample.

In the upper-left corner of the workspace, select Upload , then select one of the sources.

Select the file. Depending on where the file is, select Upload or Open .

The Power BI service uploads your Excel file.

Related content

• Basic concepts for designers in the Power BI service
• Tutorial: Explore a Power BI sample
• Data sources for the Power BI service

More questions? Try the Power BI Community

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Additional resources

Top 15 Power BI Project Ideas for Practice (2023)

In the dynamic landscape of data analysis and business intelligence, Power BI has emerged as an essential tool for businesses and professionals aiming to utilize the potential of data-driven decision-making. Whether you're a seasoned data analyst or a newcomer to the field, engaging in practical projects and hands-on experience can significantly enhance your Power BI skills. This article compiles a comprehensive list of top Power BI projects that cater to various skill levels and industries. Engaging in these Power BI projects will provide you with hands-on experience, sharpening your data analysis and Power BI skills for excellence in this dynamic field.

What is Power BI?

• Power BI, a business intelligence and data visualization platform developed by Microsoft, enables users to connect to various data sources, transform and model data, and create interactive visualizations and reports.
• With its user-friendly interface and advanced features, Power BI enables businesses to derive actionable insights from large volumes of data, make data-driven decisions, and gain a competitive edge.
• Whether analyzing sales trends, monitoring KPIs, or discovering hidden patterns, Power BI empowers users at all levels to explore, visualize, and share data seamlessly and efficiently.

What is Power BI Used For?

Here are a few of the key applications Power BI is used in organizations -

• Data Visualization - Power BI is used to create visually appealing and interactive dashboards that help present complex data in an easily understandable format.
• Business Intelligence - It enables businesses to gather insights from various data sources, aiding in informed decision-making and strategic planning.
• Data Analysis - Power BI facilitates the analysis of large datasets, enabling users to identify trends, patterns, and correlations for better understanding.
• Report Generation - It streamlines the process of generating detailed and customized reports, automating routine reporting tasks.
• Data Collaboration - Power BI allows teams to collaborate on data projects, share insights, and work collectively on data-driven projects.

How To Do Visualization in a Power BI Project?

Visualizing data effectively is a cornerstone of Power BI projects. You can begin by importing your data from various sources like databases, CSVs, spreadsheets, or online platforms. Once your data is loaded into Power BI, you can select from a wide range of visualization options, including charts, graphs, maps, and tables. You should choose the appropriate visualization type based on the nature of your data and the insights you want to convey. For instance, you could choose a column chart to showcase product sales across different months, a pie chart representing the percentage distribution of sales by product category, or a map to visualize regional sales performance.

Customization is key - you also have the flexibility to customize the appearance of your visualizations by adjusting colors, fonts, and labels to ensure they align with your project's theme and branding. For instance, if you're analyzing customer feedback, you might want to use a sentiment analysis visualization that color-codes sentiments as positive, neutral, or negative.

You can also use filters and slicers to enable interactivity, allowing users to explore data subsets and uncover specific trends. To enhance storytelling, create a dashboard by arranging multiple visualizations on a single canvas. Utilize features like drill-through and tooltips to provide additional context and detail. For instance, users could click on a particular product category to see detailed sales figures.

Regularly preview and fine-tune your visualizations to achieve clarity and impact. By mastering the art of visualization, you can transform raw data into compelling narratives that drive meaningful insights and decisions.

15 Power BI Project Examples

Within this article, you'll find a compilation of 15 Microsoft Power BI projects. These Power BI projects are organized into three tiers - beginner, intermediate, and advanced. Feel free to select any of these Power BI projects to enhance your proficiency in the realm of Data Science and Analysis through hands-on practice. Let’s explore these Power BI projects in the subsequent sections.

Beginner-Level Power BI Project Basic Examples

In this section, we've compiled a selection of Power BI projects tailored for beginners. Engaging with these simple Power BI projects will provide you with insight into the applications of business intelligence and pave the way for a prosperous journey as a budding data scientist.

Customer Churn Analysis

The Customer Churn Analysis project is a simple and popular example that helps you learn how to use Power BI. This project focuses on studying customer behavior, specifically when they churn, that is, stop using a service or buying a product. By looking at the sales and profits of products in different regions, you can understand which areas are doing well and distribute profits effectively. The goal is to determine how to keep customers engaged and prevent them from leaving. To do this, you'll create different types of visual displays, like charts and graphs, that show how sales change over time and how different products perform.

You can use a dataset from Kaggle to perform a Customer Churn Analysis that contains information about different customers. This project is perfect for beginners who want to grasp Power BI's capabilities.

Product Sales Data Analysis

Analyzing sales data is crucial for businesses to understand how well they're doing. But when there's a lot of data, it can be a hard task to keep track. This project helps companies by looking at their sales info and showing which products are making the most money.

Using a dataset provided by Microsoft , you'll connect it to Power BI and perform data cleaning to remove irrelevant records to only focus on the important info. Then, you can make visual displays like Pie Charts, Bar Charts, and more to help everyone see the sales info clearly. This way, companies can make better decisions about their products and sales strategies.

Marketing Campaign Insights Analysis

The Marketing Campaign Insights Analysis project aims to demonstrate how well different marketing campaigns and product groups are doing. It helps marketing managers understand which campaigns are successful.

You can work with a dataset from Kaggle containing marketing data. By creating a data visualization dashboard using Power BI, you can show information like how much money is spent on each category, how well campaigns are performing, and key highlights of the campaign. You can use charts like Bar Charts and Column Charts, as well as features like Smart Narratives to highlight important points. This project is great for beginners and gives marketing managers useful campaign insights.

Financial Performance Analysis

The Financial Performance Analysis is a fascinating project for people new to Power BI. In this project, you'll focus on improving how a company that offers accounting services analyzes its finances. The goal is to ensure they can quickly get the important financial data they need. This project could involve moving from using Excel for financial reports to using Power BI dashboards. This change would help clients see their financial situation better and how well they're doing. It's a great way to learn Power BI while helping a company become more efficient in understanding its finances. For this project, you can download and use the data from Kaggle .

Healthcare Sales Analysis

This Healthcare Sales Analysis project is designed for the Animal Healthcare industry to keep track of product sales for treating minor animal species. It helps businesses compare sales between different cities and see how well their products are selling. The project can create a detailed report on which types of products are selling the most and how sales are changing over time. You can use a dataset about pharmaceutical sales from Kaggle .

In Power BI, you can use different types of visuals like Tables to display sales by product type, Column Charts for monthly sales trends, and Bar Charts for comparing sales in different cities. You can also explore features like Treemaps, Cards, and Smart Narratives.

Intermediate-Level Power BI Project Ideas

If you're already familiar with the Power BI data visualization tool and are eager to enhance your data analytics skills, particularly as a Data Scientist or Data Analyst, consider these Power BI projects to enrich your resume -

Anomaly Detection in Credit Card Transactions

Our first Power BI project idea is about detecting anomalies or unusual activities in credit card transactions, known as "Anomaly Detection." Anomaly Detection is a way of using machine learning to find transactions that are different from the norm and might be suspicious. There are three methods to do this - supervised (when you have labeled data), semi-supervised (for normally behaving data), and unsupervised (for data without labels).

For this project, you can use the credit card dataset by Delaware, available on their open data platform, or the credit card fraud detection dataset from Kaggle. First, you bring the dataset into Power BI desktop, maybe using a web connector. Then, you can use Power BI to train a system to identify anomalies, or you can use a pre-trained model. To label outliers in Power BI, you'll need to run a Python script in the Power Query Editor, using the get_outliers() method from PyCaret library. Lastly, you can use Power BI Dashboard to display your findings. You could also train your anomaly detection model in another tool/IDE and then use Power BI to label the anomalies. To visualize the results, the Power BI dashboard offers various tools like Line Charts, Bubble Charts, and TreeMaps.

AutoML Cashflow Optimization for Insurance Company

AutoML, short for automated machine learning, is a method that automates the time-consuming, iterative, and complex steps of machine learning. It helps data experts quickly create effective machine learning models. The main aim of any AutoML solution is to find the best model based on how well it performs.

In this project related to business intelligence, you'll use a dataset from Kaggle about medical costs. The task is for an insurance company that wants to better predict patient expenses using factors like patient details and health risks. This way, they can manage their finances better. The first step is using Power BI Desktop to open and copy the dataset. Then, you'll run a Python script using Power Query, where you can train, compare, and evaluate performance of different models with the compare_models() method from PyCaret library. This helps you see which model works best. You can also use the automl() function to find the top-performing model. For the final dashboard, you can use Power BI to create visuals like Bar Charts, Bubble Charts, and Tables to display the results.

Global Health Expenditure Analysis

This project focuses on using clustering analysis with PyCaret in Power BI. Clustering is a way to group similar data together to understand patterns and structures.

For this project, you can work with the health spending data from the WHO Global Health Expenditure database. This dataset covers health expenses as a part of each country's GDP for more than 200 countries from 2000 to 2018. You can use the K-Means clustering algorithm to group the data. Once you load the data into Power BI Desktop and create the clustering model, you can visualize the clusters on a Power BI Dashboard. For an overview page, you can use visuals like Filled Maps and Bar Charts, while for a detailed look, you can use Point Maps. This project is a great way to learn how to use clustering to understand health spending patterns across the globe.

Analyzing Loan Applications

This project involves examining data from loan applications to uncover hidden 'topics,' which help evaluate the impact of specific loan types on the default rate. This is done by using a technique called Latent Dirichlet Allocation (LDA) topic modeling in Power BI. Topic modeling is a way to figure out the main themes in a set of documents.

For this task, you can work with the Kiva dataset available on GitHub. This dataset includes information about loans from 6,818 potential borrowers that were accepted. It contains details like loan amounts, borrower nationality, gender, and some text data from their applications. Once you bring this dataset into Power BI Desktop and train your model, you can visualize the results on a Power BI dashboard. You can use features like Word Clouds, Pie Charts, Bar Charts, and Scatter Charts to show the topics and their impact. This project helps you explore how different factors affect loan defaults using advanced techniques in Power BI.

Interactive Visualization of Movie Sales

The movie sales visualization project is a really fun Power BI project idea. The goal is to take data about how much money movies make and make it into a cool interactive display. You can use the IMDb dataset that covers the years 2006 to 2016, available on IMDb and Kaggle. This dataset has info about movies with a score of 6 or more on IMDb, including Budget, Gross earnings, Genre, and Scores.

You can make a special Radial Bar Chart and use Slicers to choose Genre, Country, and score range directly in Power BI. This lets you see things like the Average Score and how much money movies made in the selected group. By using a Histogram on the scores with filters for year and genre, you can show how often certain IMDb scores appear. A KDE plot is another neat feature that shows a density graph, helping you understand the average rating for a specific genre and how scores are distributed over time.

Advanced-Level Power BI Project Ideas

Lastly, we've compiled a selection of advanced Power BI projects with datasets, tailored for professionals seeking intriguing challenges to further elevate their Power BI skills.

Airport Authority Data Analysis

The Airport Authority Data Analysis project is all about understanding important airport information. This includes the total flights (coming and going), delays (arrivals and departures), time for ground operations, and even passenger feedback. All these details can be shown on a dashboard's main page. This project's purpose is to help airport managers make quick decisions based on data, especially during flight changes, emergencies, or delays.

To do this project, you can use the Airline Delays and Cancellation dataset from Kaggle. This dataset covers airline data from 2009 to 2018, giving insights into trends over time. For flight analysis, you can use Power BI visuals like Cards, Bar Charts, Flow Maps, TreeMaps, and Tornado Charts. To show passenger feedback, Bar Charts, Column Charts, or Cards might work well. This project gives you the chance to learn how Power BI can help manage airport operations effectively.

Covid-19 Insights Analysis

The Covid-19 Insights Analysis is a highly popular Power BI project choice. It's about taking a deep look at the key parts of the Covid-19 pandemic - the current situation and details about different countries. You'll make a dashboard that shows important info about cases (active, deceased, and recovered), mortality rates, and recovery rates for each country and over time. This dashboard might also have a summary of the main KPIs (key performance indicators) and in-depth analysis on separate pages.

For this project, use the Covid-19 dataset from Kaggle. To visualize the data in Power BI, you can use features like Bar Charts, Point Maps, Line Charts, and Column Charts for the main overview. For a closer look at case categories, Doughnut Charts work well. And if you want to analyze cases by country, Decomposition Trees are a good option. Heat Maps can also make your dashboard more informative and engaging. This project lets you learn how Power BI can help understand Covid-19 data in a meaningful way.

Construction Permit Data Analysis

The Construction Permit Data Analysis project aims to help construction companies get a deep understanding of the industry. This means looking closely at specific details and exploring important events. You can focus on things like how investments grow over time, where investments are focused, and if they're influenced by factors like Category, Contractor, or Individual. You'll also study the market's status and which categories, individuals, and permits play a big role.

For this project, use the Seattle building permits dataset from Kaggle. To visualize data in Power BI, you can use tools like Regional Maps, Pie Charts, Bar Charts, Tables, and Cards for the main page. For more details, Bar Charts and Line Charts can show how contractors compete and how different categories are growing. This project helps you see how Power BI can provide insights into the construction permit industry.

Global Energy Trade Analysis

The Global Energy Trade Analysis is one of the really unique Power BI projects. It's all about understanding the exchange and production of energy worldwide. This project touches on several areas, like the growth of wind energy and comparing economies based on energy use.

To tackle this special project, you can use the international energy statistics dataset from Kaggle. Your resulting dashboard could show energy stats on things like production, exchange, and usage of different energy sources. You'll cover both conventional and non-conventional energy sources, as well as new and renewable ones. For this dashboard, Power BI offers visuals like Bar Charts, Flow Maps, and Cards for an overview. And for specific sections, you can use Ribbon Charts, Treemaps, and more Bar Charts. This project teaches you how Power BI can provide insights into the complex world of global energy trade.

Life Expectancy Data Analysis

The Life Expectancy Data Analysis project is about understanding what affects life expectancy. It looks at things like vaccinations, deaths, money, social aspects, and other health-related factors. This helps a country figure out what leads to lower life expectancy. It also helps them decide where to focus efforts to increase how long people live.

To do this, you can use the life expectancy dataset from the World Health Organization (WHO) on Kaggle. Power BI offers visuals like Gauge Charts, Pie Charts, Line Charts, and Point Maps to give an overview. For country-specific details, you can use Tornado Charts, Doughnut Charts, and Treemaps. This project teaches you how Power BI can provide valuable insights into life expectancy and health-related issues.

Power BI Projects Github

Here are some unique and interesting project concepts from GitHub that can help you grasp the diverse ways Power BI can be used.

Twitter Analysis Dashboard

This project involves building a complete pipeline for analyzing Twitter data, from start to finish. To work on this Power BI project, you can get Twitter data from GitHub . The process involves extracting the data, changing it from JSON to CSV, and adding new attributes as needed. Using NLP analysis, you'll categorize the content of tweets and find out how positive or negative they are. Once the data is prepared, you can use Power BI to create detailed reports. To design the dashboard, you'll make use of different types of visuals like pie charts, bar graphs, line charts, tree maps, and doughnut charts, among others.

OTT Media Dashboard

This distinctive Power BI project involves displaying different kinds of data from various OTT platforms like Netflix, Hotstar, and Amazon Prime. To get started, you can obtain the OTT media platform dataset from GitHub. Use Power BI's Query Editor to clean and prepare the data. Once your data is set for visualization, you can showcase the information using a variety of visual tools like plots, graphs, cards, and more. This project helps you explore how Power BI can make OTT media data easier to understand and analyze.

AdventureWorks Database Analysis

For this project, you'll dive into the AdventureWorks data available on GitHub . The analysis and visualization process involves using Microsoft SQL Server Management Studio for querying data and Power BI for creating visual displays. Additionally, Microsoft Excel and Power BI's query editor can be used for in-depth analysis. This project helps you explore the AdventureWorks dataset and understand how to leverage various tools for analysis and visualization.

Power BI Report Examples

Here are a few compelling examples of Power BI reports that demonstrate the effectiveness of data visualization through the Power BI tool. These examples will help you comprehend the impact of using Power BI for visualizing data.

Retail Analysis Power BI Report

In this retail analysis report, you'll find a dashboard that examines sales data for products sold by different retailers across various regions. The dashboard includes insights into new store performance and a comparison between the current year and the previous year. This comparison covers key metrics like sales, units sold, gross margin, and variations.

Global Covid-19 Analysis Power BI Report

Through interactive visuals using easily accessible data, the Global Covid-19 Analysis Report provides a comprehensive view of COVID-19 trends across the globe. The report features maps that display crucial aspects like Vaccination rates, Progress toward zero cases, Rt values, Spread Analysis, Testing rates, and Risk Levels.

Inventory Stock Analysis Power BI Report

This report delves into inventory stock analysis, offering insights into stock inventory trends for the year 2018. With this interactive dashboard, you can make predictions about the "Availability of Stock" and "Time to Replenish Stock." These predictions are based on data from the fulfillment cycle and markdown variance, providing valuable insights for inventory management.

Cancer Analytics Power BI Report

The Cancer Analytics report provides both a concise overview and an in-depth analysis of cancer patients in the United States. Through this report, you can examine the mortality rates associated with various types of cancer, categorized based on multiple factors. By utilizing the Cancer Analytics Dashboard, you can make informed decisions regarding the increasing number of cancer patients in the country.

Customer Analysis Power BI Report

The Customer Analysis Report focuses on product sales and profits from local customers. This report is particularly valuable for those interested in analytics, as it provides insights into the distribution of customer profits and business expansion in different regions. The main attractions of the Customer Analysis report dashboard include visualizing cash inflow in specific regions and tracking turnover for different products among clients.

Master Data Visualization With These Power BI Projects

Whether you're a beginner or an expert, these real-time Power BI projects are designed to enhance your skills and help you master the art of integrating business intelligence into Data Science. By taking on these project ideas, you'll gain a deeper insight into using Power BI to adopt a data-driven approach across various data science fields, preparing you for potential job roles. If you're searching for free Power BI projects with solutions, platforms like GitHub or Kaggle offer great resources.

Q. What projects can I do with Power BI?

A. You can explore a wide range of projects using Power BI to enhance your data analysis and visualization skills, as mentioned in this article. If you are a beginner to the Power BI, you can work on the Customer Churn Analysis and Product Sales Data Analysis. If you are at intermediate level, then you can experiment on the Anomaly Detection in Credit Card Transactions and Movie Sales Visualization. Advanced users of Power BI can work on Covid 19 and Twitter Analysis Dashboard to elevate their Power BI skills.

Q. How do you practice Power BI?

A. The best way to practice Power BI is through hands-on experience with various projects. Start by selecting projects that match your skill level, such as customer analysis, sales data analysis, or COVID-19 insights. This practical approach not only enhances your proficiency but also equips you with real-world problem-solving abilities using Power BI's tools and features.

Q. Where can I get practice data for Power BI?

A. You can find practice data on platforms like GitHub and Kaggle, where datasets related to various domains are available for free. These platforms offer a wide range of datasets that you can use to explore and develop your Power BI skills. Additionally, the Power BI service provides pre-built sample datasets, making it convenient to start practicing directly within the platform itself.

• Power BI projects, mentioned in this article, offer a diverse range of opportunities for both beginners and professionals to sharpen their data analysis and visualization skills.
• These projects provide hands-on experience in tackling real-world data challenges, enabling you to derive valuable insights and make informed decisions.
• The projects span various industries, from healthcare to finance, giving you a chance to explore and understand data dynamics across sectors.
• By mastering Power BI through these projects, you're preparing yourself to excel in the data-driven world and become job-ready in the realm of data science and business intelligence.

13 Best Datasets for Power BI Practice

Too Long; Didn't Read

People mentioned.

In 2022, Gartner named Microsoft Power BI the Business Intelligence and Analytics Platforms leader.

With the aid of business intelligence tools like Microsoft Power BI, unstructured data can go through extraction, cleaning, and analysis processes to create insights that help organizations make data-driven decisions.

In this article, we will look at the 13 Best Datasets for Power BI Practice , which are essential in helping data professionals build their proficiency in Power BI.

List of the Best Datasets for Power BI Practice

1. sample superstore sales.

The Sample Superstore Sales dataset provides sales data for a fictional retail company, including information on products, orders and customers.

This dataset includes the following variables:

Order ID - A unique identifier for each order.

Customer ID - A unique identifier for each customer.

• Order Date - The date of the order placement.
• Ship Date - The date the order was shipped.
• Ship Mode - The shipping mode for the order (e.g. standard, same-day).
• Segment - The customer segment (e.g. Consumer, Corporate, Home Office).
• Region - The region where the customer is located (e.g. West, Central, East).
• Category - The category of the product purchased (e.g. Furniture, Technology, Office Supplies).
• Sub-Category - The sub-category of the product purchased (e.g. Chairs, Desktops, Paper).
• Product Name - The name of the product purchased.
• Sales - The sales revenue for the product purchased.
• Quantity - The number of units of the product purchased.
• Discount - The discount applied to the product purchased.
• Profit -The profit generated by the product purchased.

2. Adventure Works DW

The Adventure Works DW is a sample database for Microsoft SQL Server Analysis Services (SSAS). It offers a dimensional data model for a fictional bicycle manufacturer, Adventure Works Cycles. It also comprises information on product catalogues, sales, customer demographics and time-based data for analysis & reporting.

Customer -This includes customer demographics, such as age, gender, education, and income.

Sales - This includes sales information, such as sales territory, salesperson, and order date.

Product - This includes product categories, subcategories, and product names.

Date -This includes the date and related attributes such as quarter, month, day, and day of the week.

Geography - This includes customers' state, city, postal code and sales orders.

To download this dataset, you can click here .

3. Flight Delays and Cancellations

This real-world dataset comprises data on flight numbers, departure, airlines, arrival times and the reason for any delays or cancellations. With this dataset, Power BI users perform data analysis and create interactive dashboards to identify the most common causes of flight disruptions by studying the frequency of cancellations by airline and flight delays.

It comprises the following variables:

• Flight Duration - The length of time from departure to arrival for the flight.
• Delay Reason - The reason for any delay in the flight. Examples may include weather, mechanical issues, or air traffic control.
• Delay Time - The amount of time by which the flight was delayed.
• Cancellation Reason - The reason for cancellation of the flight.  Examples may include weather, mechanical issues, or insufficient passenger demand.
• Date of Flight - The date on which the flight took place.
• Flight Number - A unique identifier assigned to each flight by the airline.
• Airline Name - The name of the airline operating the flight.
• Departure Airport - The airport from which the flight is scheduled to depart.
• Arrival Airport - The airport at which the flight is scheduled to arrive.
• Scheduled Departure Time - The time at which the flight was scheduled to depart, as originally planned by the airline.
• Actual Departure Time - The actual time at which the flight departed, if different from the scheduled departure time.
• Scheduled Arrival Time - The time at which the flight was scheduled to arrive, as initially planned by the airline.
• Actual Arrival Time - The actual time at which the flight arrived, if different from the scheduled arrival time.

4. NYC Taxi Data

NYC Taxi Data is a rich and complex dataset that contains info on taxi trips in New York City, including trip durations, fare amounts, and pickup and drop-off locations. It covers millions of trips and spans several years, providing a rich source of information about urban mobility and transportation patterns in the city.

By analyzing this data, you can gain insights into various areas of the taxi industry in NYC. For example, you can visualize the distribution of trips over time and space, and identify hot spots of taxi activity in the city.

The dataset includes the following variables:

Trip Duration - The duration of the trip, in seconds.

Trip Distance - The distance travelled by taxi, in miles.

Number of Passengers - Total number of passengers in the taxi.

Fare Amount - The fare charged to the passenger, in dollars.

Payment Method - The method of payment used by passengers (e.g credit card, cash etc.).

Pickup and Drop-off Location - The GPS coordinates of the pickup and drop-off locations.

Trip Type - This indicates whether the trip is a dispatched trip (green taxi or for-hire) or a street hail (yellow taxi).

Pickup and Drop-off Time - The time and date at which the pickup and drop-off took place.

To download this dataset, click here .

5. Global Superstore

The Global Superstore dataset is a simulation of retail sales operations with stores in multiple countries. It includes information about customers, orders and products, which is particularly useful for exploring retail sales data, as it offers a large and diverse set of data that can be used to analyze customer behaviour, product performance and sales patterns.

Order Date - The date and time the order was placed.

Ship Date - The date and time the order was shipped.

Ship Mode - The method used to ship the order (e.g. standard, express).

Customer Name - The full name of the customer.

Segment - The customer segment such as Home Office or Corporate.

Country - The country where the customer resides.

City - The city where the customer resides.

State - The state where the customer resides.

Postal Code - The postal code of the customer's residence.

Region - The geographic region where the customer resides.

Product ID - A unique identifier for each product.

Category - The broad product category, such as Furniture, Office Supplies, or Technology.

Sub-Category - The specific product sub-category, such as Chairs, Paper, or Phones.

Product Name - The name of the product.

Sales - The total sales revenue for the product.

Quantity - The number of units of the product sold.

Discount - The discount applied to the product.

Profit - The total profit earned from the product.

6. Seattle Weather Data

This dataset is a comprehensive dataset which provides historical weather information for the Seattle, Washington area. It can be used to study the climate and weather patterns as well as weather’s impact on various industries and activities, such as tourism, agriculture and transportation.

Some of the critical variables in the Seattle Weather Data include:

• Date - The date of the observation.
• Prcp - The amount of precipitation, in inches.
• Tmax - The maximum temperature for that day, in degrees Fahrenheit.
• Tmin - The minimum temperature for that day, in degrees Fahrenheit.
• Rain - This shows TRUE if rain was observed on that day and FALSE if it was not.

7. World Bank Development Indicators

This dataset contains information on GDP, life expectancy, and literacy rates for various nations throughout the world. It also includes many economic and social variables.

Some of the variables included in this dataset are:

Gross Domestic Product (GDP)

Unemployment rate

Government debt

Trade balance

Life expectancy

Infant mortality rate

Access to electricity

Literacy rate

Mobile cellular subscriptions

Note: The variables included in the dataset depend on the year and the country being analyzed.

You can download the dataset directly from the website or you can download it on Kaggle .

8. US Health Data

The US Health Dataset provides comprehensive information on health behaviour and health status, including data on healthcare utilization, physical activity and chronic diseases. It can be used to study trends in public health and to investigate the impact of lifestyle and health behaviour on health outcomes.

The US Health Data is sourced from the Centers for Disease Control and Prevention (CDC), the National Center for Health Statistics (NCHS), and the Agency for Healthcare Research and Quality (AHRQ).

The common variables in this dataset include:

Demographic information -  Age, gender, race, and ethnicity

Health status indicators - Self-reported health, chronic conditions, and disability

Healthcare utilization measures - Hospitalizations, emergency room visits, and primary care visits

Health behaviours - Smoking, exercise, and diet

Health outcomes - Life expectancy, mortality rates, and incidence of specific diseases

Healthcare costs - Total medical expenditures, out-of-pocket costs, and insurance coverage

Access to healthcare, including insurance coverage, availability of healthcare providers, and proximity to healthcare facilities

Note: Variables included in the US Health Dataset can vary depending on the data source.

9. Stack Overflow Survey Results

Stack Overflow Survey Results contain results from the annual Stack Overflow developer survey. It includes various aspects of developer experience, such as salary and compensation, preferred technologies, work satisfaction etc. It can be used to explore and gain insights into the state of the developer community.

This dataset contains a large number of variables, including but not limited to the following:

Personal Information - Age, gender, country, and education level.

Employment - Employment of employment, company size, and job title.

Development Experience - Years of experience, primary programming language, and development environment.

Salary and Compensation - Salary, currency, and benefits.

Work Satisfaction - Job satisfaction, career satisfaction, and job search.

Technology Usage - Preferred operating system, programming language, development environment, and tooling.

Community Involvement - Contributions to open-source projects, Stack Overflow reputation, and participation in developer communities.

The dataset can be downloaded directly from the website .

10. Titanic: Machine Learning from Disaster

This popular open-source dataset offers information on the passengers onboard the Titanic ship when it sank on April 15, 1912.

Some of the variables included in the dataset:

PassengerId - A unique identifier for each passenger.

Survived: This shows whether the passenger survived or not (0 = No, 1 = Yes).

Pclass: A passenger's class (1 = 1st, 2 = 2nd, 3 = 3rd).

Name - A passenger's name.

Sex - A passenger's gender.

Age - A passenger's age.

SibSp - The number of siblings/spouses aboard.

Parch - The number of parents/children aboard.

Ticket - The ticket number.

Fare - The fare paid for the ticket.

Cabin - The cabin number.

Embarked - The port of embarkation (C = Cherbourg, Q = Queenstown, S = Southampton).

You can download the dataset on Kaggle .

11. Wine Quality

The Wine Quality dataset contains information on red and white wine samples. The goal of this Power BI dataset is to classify the quality of the wine based on chemical properties like pH, density, alcohol content and citric acid content.

The common variables included in this dataset:

Fixed Acidity - The number of fixed acids in the wine, expressed in g/dm^3.

Volatile Acidity - The number of volatile acids in the wine, expressed in g/dm^3.

Citric Acid - The amount of citric acid in the wine, expressed in g/dm^3.

Residual Sugar: The amount of residual sugar in the wine, expressed in g/dm^3

Chlorides - The amount of chloride in the wine, expressed in g/dm^3.

Free Sulfur Dioxide - The amount of free sulfur dioxide in the wine, expressed in mg/dm^3.

Total Sulfur Dioxide - The amount of total sulfur dioxide in the wine, expressed in mg/dm^3.

Density - The density of the wine, expressed in g/cm^3.

pH - The pH level of the wine.

Sulphates - The number of sulphates in the wine, expressed in g/dm^3.

Alcohol - The alcohol content of the wine, expressed in % vol.

Quality - The quality rating of the wine, on a scale of 0 to 10.

You can download the dataset from UCI Machine Learning Repository by clicking here .

12. US Crime Rates

The US Crime Rates dataset provides information on crime rates in the United States. It is organized based on geographical region, period or other relevant factors and is mostly used to analyze crime trends and patterns or as well to support criminal justice decision-making and law enforcement. It is also commonly used for exploratory data analysis and visualization and can be used to create interactive dashboards and reports in Power BI.

M - The percentage of males aged 14–24.

Po1 - The per capita expenditure on police protection in 1960.

Po2 - The per capita expenditure on police protection in 1959.

M.F - The number of males per 100 females.

You can download the dataset from Kaggle .

13. Airbnb Listings

This dataset is a collection of data on Airbnb listings, including price, amenities, type of property, number of bedrooms and location in New York City. It is commonly used for exploratory data analysis and visualization, with a focus on the distribution of listings and prices across different locations and neighbourhoods.

Id - Airbnb's unique identifier for the listing.

Host Id -  Airbnb's unique identifier for the host.

Host name - The name of the listing.

Neighbourhood Group - The neighbourhood group e.g Manhattan, Brooklyn etc.

Host identity verification - This shows if the host identity is either verified or unconfirmed.

The dataset can be accessed on Kaggle by clicking here .

Common Project Use Cases for the Power BI Datasets

Retail analytics.

Sample Superstore Sales

Global Superstore

Adventure Works DW

• Retail sales analysis, customer segmentation, product performance analysis, market segmentation and sales territory analysis.

Transportation Analytics

NYC Taxi Data

Flight Delays and Cancellations

• Taxi demand and supply analysis, trip analysis, driver performance analysis, fare comparison, flight performance analysis and airport comparison.

Weather Analytics

Seattle Weather Data

• Weather trend analysis, climate change analysis, prediction of weather patterns and impact on various industries.

Economic Analytics

World Bank Development Indicators

• Global development analysis, comparison of countries, prediction of economic trends and economic performance analysis.

Healthcare Analytics

US Health Data

Healthcare analytics, comparison of states, analysis of healthcare spending and outcome.

Workforce Analytics

Stack Overflow Survey Results

• Workforce analysis, technology trend analysis, comparison of salary and job satisfaction.

Machine Learning/Survival Prediction

Titanic: Machine Learning from Disaster

• Survival prediction, data analysis and visualizations of the Titanic disaster.

Quality Analysis

Wine Quality

Quality analysis, prediction of wine quality based on its chemical properties, wine preference analysis and recommendations.

Crime Analytics

US Crime Rates

• Crime analysis, comparison of crime rates by city, state and region, and analysis of crime patterns and trends.

Travel Analytics

Airbnb Listings

• Travel analysis, housing demand analysis, rental pricing analysis and popular tourist destination analysis.

Final Thoughts

These datasets and common use cases will help you better understand the role of Power BI in helping organizations make smarter, real-time decisions.

They are also available for anyone to download and use freely.

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Top 10 Power BI Project Ideas for Practice

What is power bi, why power bi, top power bi projects, power bi projects for beginners, 1. product sales data analysis, 2. marketing campaign insights analysis, 3. financial performance analysis, 4. customer churn analysis, intermediate level power bi project ideas, 5. global health expenditure analysis, 6. energy trade analysis, 7. anomaly detection in credit card transactions , advanced level power bi project ideas, 8. covid insight analysis, 9. airport performance analysis, 10. life expectancy data analysis, additional resources.

Data has become a ubiquitous part of business today, making it essential for businesses to understand how to gain value from the wealth of raw data available to them. The right information must be gleaned from the data and presented clearly for making well-informed business decisions. Because of this, business intelligence (BI) systems have gained tremendous traction that can assist an organization in discovering useful information, suggesting conclusions, and supporting decision-making. BI is a system that analyzes data, provides actionable information, and helps users to take informed business decisions. As a proven technology leader, Microsoft has propelled itself to the forefront with the introduction of its powerful analytics tool, Power BI. 

Microsoft’s Power BI toolkit transforms your data into meaningful information, making it one of the most popular business intelligence tools in the world. The increasing popularity of Power BI has led to an increased demand for Power BI professionals and business analysts.

Are you intrigued? If so, we’ve created this detailed guide for you. In this article, we will discuss some Power BI projects ideas that you can use to boost your chances of becoming a Power BI professional. But before we start exploring Power BI projects and Power BI projects for practice, let’s take a look at exactly what Power BI is and why it is so important.

Confused about your next job?

Power BI is a Business Intelligence and Data Visualization tool designed to analyze, visualize, and process enormous volumes of raw business data and transform them into actionable and interactive insights that help business managers, corporate executives, and other users to make better informed business decisions. Raw data can be stored in an Excel spreadsheet, cloud-based databases, or on-premises data warehouses. But, Power BI makes it easy to connect to your data sources, visualize it to find out what’s important, and share it with others. Using it, you can gain insight, draw conclusions, and share results across departments in the form of analytical reports or interactive dashboards.

Power BI is a BI solution by Microsoft that provides a simple yet powerful interface that even non-technical users can use to create dashboards and analysis reports. Besides offering easy drag-and-drop functionality, the tool also provides a range of interactive data visualizations for creating interactive reports and dashboards. Among all the apps, connectors, and services provided by the Power BI platform, the following key components stand out:

• Power BI Desktop (a Windows desktop application)
• Power BI service (an online SaaS (Software as a Service) service)
• Power BI mobile applications (available for different platforms such as Windows, iOS, and Android devices)

With these three elements, you can build, exchange, and leverage business insights in a way that’s efficient and impactful for any business.

Now that you know what Power BI is, let’s look at what makes it so valuable for analytics.

The following are some of the reasons why Power BI is widely considered one of the best business intelligence tools worldwide:

• Integrates seamlessly with existing systems: Power BI enhances analytics and reporting capabilities by seamlessly integrating with your existing business processes.
• Connect seamlessly with data sources: Power BI can connect to a variety of data sources, making it possible to align data sets from different sources and generate compelling reports on the basis of that data. Over 70 connectors are available for extracting data from sources like Azure Data Warehouse, , Excel, CSV, OneDrive, Google Analytics, Dropbox, SQL databases.
• No memory or speed constraints: Migrating a BI system to a robust cloud environment with Power BI integrated does not create memory or speed constraints, enabling the data to be retrieved and analyzed efficiently. Power BI uses the pivot data modeling engine, a columnar database that reduces data sizes from about 1GB to about 200MB, thereby improving performance.
• Reports published securely: Power BI automatically refreshes data and publishes reports securely, ensuring that you always have access to the latest information.
• Custom visualization: PowerBI offers a variety of predesigned data visualizations allowing you to create interactive reports or dashboards. In addition, we can add customized visualizations created by Power BI community members to enhance the reports.

Next, let’s talk about Power BI project ideas you can work on and include in your portfolio. Furthermore, these projects allow you to practice and acquire practical experience with the various tools used for data visualization.

In order to help you broaden your knowledge and enhance your skills in Power BI, we have listed 10 Power BI project ideas based on your level of expertise. Newbies can browse through the list of Power BI projects ideas for beginners, whereas intermediates and advanced users can browse through the list of Power BI projects for intermediates and advanced users. For practice, you can select any of these power bi projects for upskilling in the Data Science space and improving portfolio. 

For beginners, it’s important to improve data analytics and visualization skills, as well as how to use different techniques to make reports more appealing. Here are some Power BI project ideas for beginners:

Businesses should keep detailed records of their sales because these records can provide valuable insight into how well their business is performing, which items are proving successful, and what changes can be made. Businesses with good records are more likely to succeed. The problem arises when there is a lot of data, and keeping track of everything can become a challenge. This is where Power BI came into play. 

Using Sales Data Analysis Project, companies are able to keep track of their sales and get answers to all of their questions about how they performed. As part of this project, we’ll be visualizing Microsoft’s sample dataset to show a profit by product and sales, as well as other key factors that may affect a company’s performance. However, the data set needs to be connected to Power BI Desktop so that irrelevant data can be removed before visualization and exporting of the filtered data as dashboards. There are various Power BI visualization types you could use for the dashboard, including Pie Charts, Bar Charts, Doughnut Charts, Funnel Charts, etc. Using the same sample dataset (Microsoft’s sample dataset), more Power BI projects can be developed and advanced visualizations can be made.

Source Code: Sales Analysis

An effective marketing campaign is a great way to reach consumers, clients and leads. An analysis of your campaign data can provide you with valuable insight into your target audience, marketing channels, and budget. Then you can figure out how (or how not) to run your next campaign. This is where Power BI came into play.

We propose this project to show off the efficiency of various marketing campaigns and the features performance analysis of products and platforms can be done. ​You can use this project to assess the success of marketing campaigns and various activities carried out under his management. This beginner-level project can be done with the Marketing Analytics dataset (this project provides insight into the customer’s profile preferences and channel performance). This dataset can be used for EDA, statistical analysis, and visualizations.  A Power BI dashboard could have several types of visualization, such as Bar Charts for category-wise expenditures, Smart Narratives for highlighting key aspects of the campaign, Bubble Charts for customer-wise spending, Column Charts for campaign success rates, Cards for highlighting individual insights, etc.

Source Code: Marketing Campaign Analysis

Microsoft Power BI is used for financial analysis to gather and analyze KPIs (Key Financial Indicators), charts, and financial statements. The purpose of this BI project is to optimize financial reporting in a firm that provides accounting services to clients seeking timely delivery of critical financial reports. Through this analysis, you will be able to access reliable financial reports quickly and efficiently. Multi-company financial datasets may be utilized for this project. 

The project outlined here can also be applied to the migration of traditional financial reporting from Excel to BI dashboards, allowing customers to track their financial health and productivity more effectively. ​In this project, Power BI data visualization options can be utilized for three scenarios as given below: 

• Funnel charts, combo charts (such as column charts, waterfall charts, line charts) for the summary page or overview page; 
• Cards, Funnel Charts, and Combo Charts (such as Line Charts and Column Charts) for the income statement page; 
• Cards and Tables for the balance sheet page.

Source Code: Financial Analysis

A major challenge that modern enterprises face is customer migration (churn). Churn, or customer attrition, is the act of customers stopping purchasing from a business or interacting with it. What can we do to overcome this challenge? The idea is to know the reasons why customers churn, the factors that impact that, so that appropriate measures can be taken to retain them. This is where Power BI comes into play.

Through this Customer Churn analysis project, one can uncover what causes your customers to stop using your product or service. Business leaders, managers, or analytical users can use this Power BI project to analyze regional business growth and the profit distribution among customers. With the right visualization and data structure, they can receive extensive data. As part of the project, regional cash inflows will be considered, as well as product-specific churn over the course of time. To complete this beginner-friendly project, you will need the customer segmentation dataset .  ​In this project, Power BI data visualization options can be utilized for different scenarios as given below: 

• Combo Charts, Bar Charts, Line Chart, Cards, Tables, etc., for overview page.
• Column Charts, Bubble Charts, Point Maps, Tables, etc., for the customer segmentation page.

Source Code: Customer Churn Analysis

You may already be familiar with the Power BI tool and are interested in strengthening your skills further as a Data Scientist . Check out these Power BI project ideas for your resumes:

A global health expenditure analysis provides comparative data on health expenditure for 192 countries over the last two decades. In this project, PyCaret (Machine learning library in Python) is used for implementing clustering analysis in Power BI. Clustering involves gathering data items having similar features. These classifications aid in examining datasets, detecting patterns, and analyzing data, while data clustering assists in identifying underlying data structures.

For this project, you can use the current health expenditure dataset from the WHO (World Health Organization) Global Health Expenditure Database. You could also use the K-Means algorithm to conduct your clustering analysis. Once the dataset has been loaded in Power BI Desktop and trained your clustering model has in Power BI, you can visualize the cluster labels in Power BI Dashboard in order to gain insights. You might choose visualization chart types such as Bar Charts, Filled Maps, etc., for the summary page dashboard, while you can use Point Maps for the detailed visualization.

In this project, various aspects of global energy production and exchange are covered. Several topics are analyzed in this project, including the expansion of wind energy the use of energy consumption to compare national economies, and many more.

Make use of the international energy statistics dataset for this project idea. ​ As a result of this effort, Power BI dashboards will display total energy statistics, including production, exchange, and usage of primary/secondary energy, new/renewable energy sources, as well as conventional/non-conventional energy sources. ​In this project, Power BI data visualization options can be utilized for different scenarios as given below: 

• Bar Charts, Cards, Flow Maps, etc., for the overview/summary page; 
• Bar Charts, Ribbon Charts, Treemaps, etc., for the energy production and exchange pages, etc.

Credit cards are being used more and more these days, which has led to an increase in fraudulent transactions (unauthorized access to an individual’s accounts or payments). Credit card fraud detection is one of the most important applications of anomaly detection. This is where Power BI comes into play. Anomaly Detection in Credit Card Transactions Project is basically a method used to identify the suspicious occurrence of data or events (outliers) that may pose problems for the concerned authorities. It is a machine learning technique used to find unusual events, things, or observations that seem suspicious during credit card transactions. There are three ways you can apply this method as given below: 

• Semi-supervised (for trained datasets)
• Unsupervised (for datasets without any labels)
• Supervised (for labeled datasets) 

If you are working on this project, you can either use the card fraud detection dataset or the credit card dataset. The first step is to import the dataset into the Power BI desktop, possibly through a web connector. Power BI can then be used to train your anomaly detector or you can use a pre-trained model. Outliers in Power BI can be labeled by running a Python script in the Power Query Editor and then using the get_outliers() method. After that, the Outliers can be visualized in Power BI Dashboards.  Line charts, bubble charts, treemaps, etc., are all can be used in Power BI dashboards for data visualization.

Source Code: Credit Card Fraud Detection

Finally, we’ve listed a few Power BI project ideas for professionals who are looking for some interesting projects to work on:

Covid-19 wreaked havoc on the entire human civilization, which we all know. Due to the sudden outbreak across all countries, global leaders were forced to take drastic measures to prevent the disease from spreading. This is where Power BI comes into play.

This Covid insight analysis project seeks to provide a comprehensive overview of the pandemic’s essential parameters and a detailed account of the situation at the national level. A Power BI dashboard can be created which displays valuable information regarding active cases, deceased cases, and recovered cases, as well as mortality and recovery rates by nation and timeframe. A dashboard can even provide a detailed analysis of the individual report pages, along with a management summary of the most important KPIs. It is an excellent project and makes you aware of how things are going. Heat Maps can also be used to enhance the dashboard visualization of your project.

For this project idea, you can use the Covid-19 dataset. As given below, Power BI data visualization options can be used for different scenarios in this project: 

• Bar Charts, Point Maps, Line Charts, Column Charts, etc., for the overview page
• Doughnut Charts for category-wise case analysis 
• Decomposition Trees for country-wise case analysis

Source Code: Covid Analysis

Globally, the aviation industry saw massive growth in passenger numbers. Right now, there are over 5,000 aircraft taking passengers and cargo around the world. However, maintaining these flights requires a lot of planning and quick decision-making. This is where Power BI comes into play.

In the Airport Authority Data Analysis project, airport data will be analyzed to provide a clear picture. On the summary page of Power BI dashboards, you can see the number of flights (incoming and outgoing), the number of delays (arrivals and departures), feedback from passengers, and ground processing times. Airport management authorities could use this type of analysis to make timely decisions when flight changes, emergencies, or delays occur. The Airline delays and cancellation dataset can be used for this project idea. As given below, Power BI data visualization options can be used for different scenarios in this project: 

• Cards, Bar Charts, Tornado Charts, TreeMaps, Flow Maps, etc., for flight analysis. 
• Column Charts, Cards, Bar Charts, etc., for the passenger feedback.

A key metric for measuring population health is life expectancy. It is beneficial to analyze life expectancy data when considering the health of a population, its characteristics, and when studying human diseases and natural population fluctuations. This is where power BI comes into play.

In the Life Expectancy Data Analysis project, factors like immunizations, mortality, finances, social issues, and other health-related issues will be considered. This will allow countries to determine the predicting factor impacting a lower life expectancy. It will also be useful in helping a country determine which areas should be prioritized to increase life expectancy. For this project, you can utilize the WHO  life expectancy dataset . As given below, Power BI data visualization options can be used for different scenarios in this project: 

• Pie Charts, Gauge Charts, Line Charts, Point Maps, etc., for the overview page 
• Treemaps, Doughnut Charts, Tornado Charts, for depicting country-wise data, etc.

Source Code: Life Expectancy

Power BI is one of the most powerful business intelligence tools for analyzing and visualizing data. Throughout this article, we discussed what Power BI is, why it is important, and the top 10 Power BI project ideas you can implement to improve your data analysis and visualization skills. Power BI project examples generally aid companies in gaining actionable insights from better visualization of their data. Using Power BI, users can create interactive dashboards and share them across the internet. Power BI also allows you to collaborate with other users and stakeholders on separate projects.

These Power BI project ideas will allow beginners, intermediates, and professionals to hone their skills and learn how to truly integrate business intelligence and data science. ​As you work on these project ideas, you’ll gain a greater understanding of how Power BI can be used for a data-driven approach towards various data science industries.

Is Power BI going away?

Sol: Power BI is one of the most popular business intelligence tools in the world that converts data into meaningful information, and therefore its popularity will never dwindle. In addition, it is a Microsoft product, which has been a dominant force on the market worldwide. It will continue to be one of the most competitive BI tools among its rivals like Tableau, Qlik Sense, etc. 

Is Power BI used for project management?

Sol: Yes, it is possible to use Power BI for project management. Essentially, Power BI is a tool that delivers actionable insights for business leaders and project managers based on internal and external research data. Through Power BI, project managers can gain a clearer picture of their projects, track them more effectively, eliminate manual report generation, and devote more time to their teams.

Is Power BI a good career?

Sol: As the leading business analytics tool among all BI tools, Power BI is a key contender. The increasing popularity of Power BI has led to an increased demand for Power BI professionals. Among the highly sought-after Power BI career prospects are Power BI developers, consultants, and analysts. As such, Power BI has a bright future and is a popular career field to switch into

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Power BI Projects and Use Cases

PowerBI is the collection of different apps, connectors, and software services that work together for transforming unrelated data sources into interactive and visually immersive insights. Our PowerBI Projects are curated to give you the real-time experience of transforming the data sources and building customised and interactive PowerBI Dashboards and Reports.

Industrial data is believed to be 'unstructured' in about 80% of cases. According to a survey published by GlobalNewswire, the worldwide business intelligence industry is expected to reach USD 33.3 billion by 2025. The tremendous growth of the business intelligence market can be attributed to a number of factors, including an increasing focus on digital transformation, more financing for analytics, high demand for data visualization dashboards, greater cloud usage, and increased data generation. This has made data insights, increased data quality, and correct data condensed in a single document even more important. Businesses that want to make the most of their data should invest in a business intelligence solution.

Are you interested in learning more? If that's the case, we've put together several Power BI Project Ideas in this article to help you improve your possibilities of becoming an expert in Power BI. But first, let's define Power BI and why it's so crucial before we begin looking at Power BI projects.

Power BI Projects - Table of Contents

What is Power BI?

Why Power BI?

Power BI Projects

Power BI Project Ideas For Beginners

Power BI Project Ideas For Intermediate Level

Advanced Level Power BI Project Ideas

Power BI is a set of apps, connectors, and software services that work together to turn unstructured data into logical,  interactive insights, and visually immersive. Your data can be in the collection of on-premises hybrid data warehouses and cloud-based or in the form of an Excel spreadsheet. Power BI makes it easier to establish a connection with your data sources, visualize and uncover what is important, and produce your results to whomever you want.

Power BI is made up of multiple components that function together, beginning with these three fundamentals:

• Power BI Desktop is a Windows desktop application.
• Power BI mobile applications are available for Android,  iOS, and Windows.
• The Power BI service is a Software-as-a-Service (SaaS) application.

These three Power BI components are intended to assist you in producing, disseminating, and consuming business insights in the most efficient manner possible for you and your role.

Apart from those three, Power BI has two more features:

• You can use the Power BI Report Builder to create paginated reports that you can distribute via the Power BI service.
• After developing your Power BI reports in Power BI Desktop, you can publish them to Power BI Report Server, which is an on-premises report server.

Power BI is regarded as one of the greatest Business Intelligence(BI) tools in the world for the following reasons:

• Connecting to data sources is simple : A wide range of data sources are supported by Power BI, allowing users to more easily match data sets from various sources and use them to create visually appealing reports. It contains more than 70 connectors which can extract data from Google Analytics, Azure Data Warehouse , CSV, Excel, OneDrive, SQL databases, Dropbox, and other sources.
• High Performance : The Power BI pivot data modeling engine is a columnar database that shrinks original data sets from 1GB to 200 MB, significantly improving performance metrics.
• Custom Visualisation : Power BI has a large number of pre-designed data visualizations that can be used to build interactive reports. Custom visualizations generated and produced by in-house developers in the Power BI community can also lend a special touch to the reports.
• R Integration for Advanced Analytics : Thousands of packages specializing in visualization and data mining are available in R, the programming language. R is a programming language used by data scientists for complex data modeling, statistical computation, and machine learning. We can import data models generated in R directly into Power BI dashboards and turn them into visualizations.
• Integration with Cortona : Microsoft's digital assistant Cortana is also supported by Power BI, allowing users to ask questions about data and access dashboard content using their voice. Users on mobile devices can even create many views by merely speaking or typing their queries.

Best Power BI Projects

Let's have a look at some Power BI project examples that you can construct and mention in your resume or portfolio. These projects can also be used to practice and gain hands-on experience with the different Data Visualisation Tools .

# 1. Analysis of the Energy Trade

Various areas of global energy production and exchange are explored in this study. This project examines a number of themes, including the rise of wind energy and the use of energy consumption to compare country economies, among others.

For this research proposal, make use of the international energy statistics dataset. As a result of this work, Power BI dashboards will provide overall energy statistics, such as primary/secondary energy production, trade, and usage, as well as new/renewable energy sources and conventional/non-conventional energy sources. Power BI data visualization tools can be used in this project for a variety of scenarios, as seen below:

For the overview/summary page, flow maps, use cards, bar charts, and so on, for the energy production and exchange pages, use bar charts, treemaps, ribbon charts, and so on.

# 2. Analysis of Financial Performance

For financial analysis, Microsoft Power BI is used to collect and evaluate KPIs (Key Performance Indicators), financial statements, and charts. This BI project's goal is to improve financial reporting in an organization that offers client accounting services that require crucial financial reports delivered quickly. You will be able to swiftly and easily access solid financial reports as a result of this study. This project may make use of multi-company financial datasets.

The project described here can also be used to migrate from Excel to BI dashboards for traditional financial reporting, allowing clients to keep a better watch of their financial health and productivity. The following three scenarios can be used using Power BI data visualization choices in this project:

• For the summary page or overview page, combo charts and funnel charts (such as line charts, column charts, and waterfall charts) are recommended.
• For the income statement page, use Funnel Charts, Cards, and Combo Charts (such as Column Charts and Line Charts).
• For the balance sheet page, there are tables and cards.

# 3. Detecting Anomalies in Credit Card Transactions

Credit cards are increasingly being utilized, resulting in a rise in fraudulent activities (unauthorized access to an individual's payments or accounts). One of the most crucial uses of anomaly detection is credit card fraud detection. Here is where Power BI enters the picture. Credit Card Transaction Anomaly Detection Project is a method for detecting suspicious events (outliers) or data that could cause issues for the concerned authorities. It's a machine learning technique for detecting unexpected things, occurrences, or observations while making credit card purchases that appears suspicious. This approach can be used in three different ways, as shown below:

• For trained datasets, semi-supervised.
• For datasets with no labels, unsupervised learning is used.
• For labelled datasets, supervision is required.

You can utilize either the credit card dataset or the card fraud detection dataset if you're working on this project. The first step is to load the dataset into the Power BI desktop , which can be done using a web connector if necessary. You can then use Power BI to train or apply a pre-trained model to detect anomalies. In Power BI, you can find outliers that can be labelled using the get outliers() method after executing a Python script in the Power Query Editor.

The Outliers can then be visualized using Power BI Dashboards. Bubble charts, Line charts, treemaps, and other data visualization tools may all be found in Power BI dashboards.

# 4. Analysis of Marketing Campaign Insights

A well-executed marketing campaign is an excellent approach to reaching out to potential customers, leads, and clients. An examination of your campaign statistics might reveal important information about your marketing channels, budget, and target audience. Then you'll be able to figure out how to carry out your next marketing campaign (or how not to conduct it). Here is where Power BI stepped in.

We recommend this project to demonstrate the effectiveness of different marketing campaigns as well as the characteristics of product and platform performance analysis. This project can be used to evaluate the marketing campaign's success and other activities that are carried out under his supervision. The Marketing Analytics dataset can be used for this beginner-level project (This project gives information on the channel's performance and customer preferences).

EDA, visualizations, and statistical analysis are all possible with this dataset. Smart Narratives for emphasizing key components of the campaign, Cards for highlighting individual insights, Bar charts for spending by category, Customer-specific expenditure bubble charts, Campaign success rates in column charts, and so on may all be included in a Power BI dashboard.

# 5. Analyzing Data on Life Expectancy

Life expectancy is an important indicator for assessing population health. When assessing the health of a population, its characteristics, and researching human diseases and natural population fluctuations, it is important to analyze life expectancy data. This is where Power BI enters the picture.

Mortality, Immunizations, finances, social issues, and other health-related topics will all be considered in the Life Expectancy Data Analysis study. This will enable countries to identify the determinant of a shorter life expectancy. It will also assist a country in determining which areas should be targeted in order to improve life expectancy. You can use the WHO life expectancy dataset for this project. Power BI data visualization tools can be used for a variety of scenarios in this project, as seen below:

• For the overview page, you can use gauge charts, line charts, pie charts, point maps, and so forth.
• For displaying statistics by country, use Doughnut Charts, Treemaps, and Tornado Charts.

# 6. Analysis of Airport Performance

Passenger numbers in the aviation industry increased dramatically over the world. Currently, approximately 5,000 aircraft transport passengers and goods around the globe. Keeping these flights running these flights(Maintaining), on the other hand, demands swift decision-making and a great deal of planning. Here is where Power BI enters the picture.

Airport data will be studied in the Data Analysis of Airport Authority project to provide a comprehensive picture. The count of flights (outgoing and incoming), the count of delays (departures and arrivals), passenger comments, and ground processing times are all displayed on the summary page of Power BI dashboards. When flight adjustments, crises, or delays occur, This type of analysis could be used by airport management agencies to make fast choices. This project proposal can make use of the Airline Delays and Cancellations dataset. Power BI data visualization tools can be used for a variety of scenarios in this project, as seen below:

• For flight analysis, use cards, tornado charts, bar charts, flow maps, treemaps, and other visual aids.
• For passenger input, use column charts, bar charts, cards, and other visual aids.

# 7. Analysis of Global Health Expenditures

Over the last two decades, analysis of global health expenditure has provided comparative statistics on 192 countries' health spending. PyCaret (a Python machine learning library) is utilized in this project to implement Power BI clustering analysis. Clustering is the process of accumulating data objects with similar characteristics. Data clustering aids in finding underlying data structures, whereas these classifications aid in detecting patterns, reviewing datasets, and analyzing data.

The World Health Organization’s (WHO) current health expenditure dataset, i.e Global Health Expenditure Database can be used for this project. You might also perform your clustering analysis using the K-Means technique. After you've loaded the dataset into Power BI Desktop and then train your clustering model in Power BI, you can use Power BI Dashboard to display the cluster labels and obtain insights. For the summary page dashboard, you may use visualization chart kinds like filled Maps,  Bar Charts, and so on, while for the deep visualization, Point Maps can be used.

# 8. Analysis of Covid Insights

Covid-19 wreaked havoc on humanity's entire civilization, as we all know. Global leaders were obliged to take urgent steps to prevent the sickness from spreading due to the rapid breakout across all countries. This is where Power BI enters the picture.

This Covid insight analysis project aims to provide a full explanation of the situation at the national level as well as a comprehensive summary of the pandemic's important parameters. A Power BI dashboard that presents useful information on active cases, deceased patients, and recovered cases, as well as mortality and recovery rates by nation and timeframe, may be created.

A dashboard can potentially provide a deep examination of individual report pages, as well as a management summary of the key performance indicators. It's a fantastic project that keeps you informed about how things are progressing. Heat Maps can also be utilized to improve the representation of your project's dashboard.

You can utilize the Covid-19 dataset for this project concept. Power BI data visualization tools can be used for a variety of scenarios in this project, as seen below:

• For the overview page, you can use point maps, bar charts, column charts, line charts, and so on.
• Doughnut charts for a case analysis by category.
• Decomposition Trees for Case Analysis by Country.

# 9. Analysis of Customer Retention

Customer migration is a big concern for modern businesses (churn). Customer attrition, often known as churn, occurs when customers cease buying from or interacting with a company. The goal is to understand why consumers leave, as well as the variables that influence their decision so that suitable actions can be done to keep them. This is where Power BI enters the picture.

This Customer Churn Analysis study will help you figure out why customers cease using your product or service. This Power BI project can be used by business executives, managers, or analytical users to analyze regional business growth and profit distribution among customers. They can obtain a lot of information if they use the correct display and data structure.

Regional cash inflows, as well as product-specific churn over time, will be considered as part of the study. You'll need the customer segmentation dataset to do this beginner-friendly project. Power BI data visualization tools can be used in this project for a variety of scenarios, as seen below:

• For the overview page, there are combo charts,  line charts, bar charts, tables, cards, and so on.
• For the customer segmentation page, there are bubble charts, column charts,  tables, point maps, and so forth.

# 10. Analysis of Product Sales Data

Businesses should retain accurate sales records because they can give them significant insight into how well their firm is operating, which things are proving to be profitable, and what changes they can make. Businesses with an excellent track record have a better chance of succeeding. The issue develops when there is a large amount of data to keep track of, making it difficult to keep track of everything. This is where Power BI stepped in.

Companies can keep track of their sales and obtain answers to all of their inquiries about how they fared with the Sales Data Analysis Project. We'll use Microsoft's example dataset to visualize profit by product and sales, as well as other important elements that can affect a company's performance. However, the data collection must be connected to Power BI Desktop in order for irrelevant data to be deleted before the filtered data can be visualized and exported as dashboards. For the dashboard, you can use  Doughnut Charts, Pie Charts, Funnel Charts, Bar Charts, and other Power BI visualization types, such as Pie Charts, Bar Charts, Doughnut Charts, and Funnel Charts. More Power BI projects and complex visualizations can be created using the same sample dataset (Microsoft's sample dataset).

Advanced Level Power BI Project Ideas For Practice

# 11. insurance company cashflow optimization with automl.

Automated Machine Learning (AutoML) is a technique for automating the time-consuming, iterative processes of Machine Learning . It allows data scientists and analysts to quickly build machine learning models while maintaining model quality. The ultimate goal of any AutoML system is to choose the best model based on a set of performance metrics.

You can use the Kaggle medical cost personal dataset in this project. The business problem includes an insurance company that wants to enhance its cash flow estimates by accurately anticipating patient charges at the time of hospitalizations using demographic and primary patient health risk indicators. The first step is to open the Power BI Desktop, then load and duplicate the dataset. After that, the Python script can be run in Power Query, where the compare models() method may be used to train, compare, and assess alternative models.

You can also use the automl() function to discover the model that performs the best out of them all. You can use Power BI dashboard tools like Bar Charts, Bubble Charts, Tables, and more to create the final dashboard.

# 12. Visualization of Film Sales

The Movie Sales Visualization project's goal is to turn a dataset depicting movie sales over time into an interactive visual experience. You can utilise the IMDb dataset, which is available on both IMDb and Kaggle, for the years 2006 to 2016. A list of movies with an IMDb score of 6 or higher, as well as the characteristics Budget, Gross, Genre, and Scores, are included in the dataset.

To be connected directly into PowerBI, you can design a custom Radial Bar Chart and use Slicers to select Genre, Country, and score range. For the selected set, this would show parameters like Average Score and Gross Collections. Alternatively, drawing a Histogram on the score variable using year and genre as slicers will provide the IMDb score frequency distribution. A density graph and insights into the average rating for a specific genre and distributions over a given timeframe can be obtained from a KDE plot.

# 13. Analysis of Healthcare Sales

The goal of the project is to make it easier for those in the Animal Healthcare industry to keep track of the sales of items used to treat minor animal species. Businesses can compare product sales in the top-ranking and bottom-ranking cities in real-time. The project could create a detailed report on sales by therapeutic group and sales trends for any given time period.

On Kaggle, you can look at the pharmaceutical sales dataset. Tables for displaying therapeutic group-wise sales; Column Charts for monthly sales trends; Bar charts for top and bottom-ranking cities; and Treemaps, Cards, Smart Narratives, and other data visualization options available in Power BI. You can also look for beginner-friendly power bi project examples in the Microsoft Power BI community.

# 14. Examination of a Loan Application

This project concept involves analyzing loan application data to identify abstract 'themes,' which are then utilized to determine the impact of specific subjects (loan kinds) on the default rate. It is built on using Power BI to create the Latent Dirichlet Allocation (LDA) topic, model. The goal of topic modelling is to evaluate a collection of texts and automatically find the abstract 'themes' within them.

You can use the Kiva dataset, which is available on GitHub and contains loan data for 6,818 accepted potential borrowers, for this project. The information includes the loan amount, country, gender, and some text data from the borrower's application. After you've trained your model and added the topic weights to the original dataset in Power BI, you can view it using the Word Cloud tool, Pie Charts on basic maps, Scatter Charts, Bar Charts, and so on in the Power BI dashboard.

# 15. Data Analysis for Construction Permits

The goal of the project is to enable construction companies to have a better understanding of the business by allowing them to go deeper into the details and investigate significant instances. You can narrow down your project to specific details like investment growth over time, investment concentrations in specific areas, whether the investment is influenced by Category, Contractor, or Individual, market status, and which categories, individuals, and permits are driving the market forward.

Use Kaggle's Seattle building permits dataset for this project proposal. Regional Maps, Pie Charts, Bar Charts, Tables, Cards for the main page, Bar Charts, and Line Charts for illustrating contractor competitions and category-wise growth, and so on can be used to visualize data in Power BI.

Power BI is a business intelligence application that allows you to analyze and visualize data. We went over what is Power BI, why it's important, and the top Power BI project ideas to hone your visualization abilities and data analysis throughout this article. In general, examples of the Power BI projects assist businesses in getting actionable insights from enhanced data visualization. Users may construct dynamic dashboards and share that across the internet with Power BI. Also Power BI allows you to work on separate projects with additional stakeholders and users.

Intermediates, Beginners, and professionals will be able to hone their abilities and learn how to truly combine data science and business intelligence with these Power BI project ideas. You'll develop a better knowledge of how Power BI may be utilised for a data-driven approach to different data science sectors as you work on these project ideas.

Madhuri is a Senior Content Creator at MindMajix. She has written about a range of different topics on various technologies, which include, Splunk, Tensorflow, Selenium, and CEH. She spends most of her time researching on technology, and startups. Connect with her via LinkedIn and Twitter .

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Home » Data Science » Power BI Projects

Top 15 Power BI Projects for Beginners, Intermediates, & Advanced Professionals

Power BI has more than 40 million monthly active users due to its robust analytics capabilities and attractive visuals that can help you sift through a mountain of data, understand it thoroughly, and make smart decisions. It is a group of several software services, connections, and apps that collaborate to transform disparate data sources into immersive and interactive visualizations. 

PowerBI projects provide you with the opportunity to convert data sources and create individualized, interactive PowerBI dashboards and reports in real-time. In this blog, we will look at some of these projects for beginners, intermediates, and advanced.

Table of Contents

What is Power BI?

Power BI is a combination of apps, connectors, and software services that can help transform unstructured data into visually engaging, logical, and interactive insights.

Your data may be stored in a collection of cloud-based and on-premises hybrid data warehouses as well as in an Excel spreadsheet. Connecting your data sources, identifying what is relevant, and producing your findings are all made simpler with Power BI. You can learn more about Power BI and how it can be used in projects by pursuing a Power BI course .

Three principles serve as the foundation for all other components that make up Power BI. These include:

• Windows desktop software called Power BI Desktop.
• Power BI mobile applications for Windows, iOS, and Android.
• Software-as-a-Service (SaaS) is a term used to describe the Power BI service.

Beginner-Level Power BI Projects

Given below are some Power BI sample projects for beginners. You can learn about business intelligence applications and have a rewarding career as a data scientist by completing these straightforward Power BI tasks.

Also Read: Power BI Interview Questions

1. Study of Customer Churn

One of the simplest and most well-liked Power BI sample projects is the customer churn study project. Customer churn analysis reveals regional customers’ product sales and earnings.  Analytical users can use it to analyze regional business expansion across geographies to divide profits among clients and get insightful information. Upon employing the correct visuals and data structures, they can receive a lot of information. 

The project takes into account local financial inflows and recurring product-specific consumer attrition. You can use the Kaggle customer segmentation dataset for this easy-to-understand exercise. You can also use combo charts, cards, bar charts, tables, or line charts for the analytical overview page, and column charts, bubble charts, point maps, tables, etc. for the customer segmentation page.

2. Examination of Product Sales Data

For many reasons, businesses keep thorough records of their sales. Yet, if there is an excessive amount of data, it becomes challenging to keep track of everything. Analyze the sales data of a company to determine profit by product, sales, and other major aspects that might have an impact on a company’s performance.

Microsoft’s sample dataset is available for use. Before visualizing and exporting the filtered data as dashboards, connect the data set to Power BI Desktop. This step will eliminate irrelevant data. The dashboard may include pie charts, bar charts, and doughnut charts, among other Power BI visualization styles.

3. Study of Healthcare Sales Among Animals

This project is for people working in the animal healthcare industry to effectively monitor the sales of goods used to treat small animal species. Companies may quickly compare product sales between cities with the highest and lowest rankings. The project could produce a comprehensive report on sales by therapeutic group and the sales trends for any given time frame.

You can consult the Kaggle-hosted pharmaceutical sales dataset. To create a data visualization in Power BI, use the following features:

• Tables for displaying therapeutic group-based sales
• Column charts for monthly sales trends
• Bar charts for top and bottom-ranking cities
• Treemaps and cards for smart narratives

For user-friendly Power BI resources for beginners, you can also visit the Microsoft Power BI Forum .

4. Inventory Management Dashboard

In this project, you will create an interactive dashboard that will help show inventory levels, reordering triggers, and turnover rates. The aim is to enable a company to reorder timely and maintain inventory. 

Use Kaggle’s inventory dataset with product details, stock quantities, sales history, and reorder levels as the base of this project. You can create columns for reordering suggestions, calculate stock turnover rates, identify low-stock products, and forecast reorder quantities.

5. Website Traffic Analysis

It is a popular Power BI project that aims to analyze website traffic to understand traffic sources, user behavior, and trending content. These insights will help a company create prompt content according to the target audience and strategize investments in successful traffic sources. 

Utilize the dataset with details like user sessions, engagement, page views, and referral sources. You can use it to identify the best referral sources, analyze page views by URL, calculate bounce rate, and derive average session duration.

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Intermediate-Level Power BI Projects

Here are some Power BI projects if you are already familiar with the Power BI data visualization tool. With the help of these projects, you can improve your data analytics abilities as a data scientist.

6. Study of Global Health Expenditures

The Global Health Spending Analysis is among the best Power BI project ideas. Using PyCaret, this project implements clustering analysis in Power BI. Data elements with comparable features are grouped using the clustering technique. These categorizations support data analysis, pattern detection, and study of datasets. Data clustering supports the discovery of underlying data structures.

Use the WHO Global Health Expenditure database’s most recent health expenditure dataset in this situation. The dataset includes health spending as a proportion of national GDP for more than 200 countries from 2000 to 2018. 

The K-Means clustering algorithm is another option for the clustering analysis. When you have loaded the dataset in Power BI Desktop and trained your clustering model in Power BI, visualize the cluster labels in Power BI Dashboard to obtain insights. You can select visualization chart kinds for the summary page dashboard, such as filled maps, bar charts, etc. while using point maps for deeper visualization.

7. Analysis of Loan Applications

The idea behind this project is to analyze loan application data to identify abstract themes, which will subsequently determine how particular subjects (loan kinds) affect the default rate. The topic model works using Latent Dirichlet Allocation (LDA) in Power BI. The goal of topic modeling is to automatically identify the abstract “themes” of a group of documents.

You can use the Kiva dataset on GitHub for this project, which contains loan information for 6,818 accepted potential borrowers. Once the topic weights are added to the original dataset in Power BI , you may load the dataset into the Power BI desktop.

Also Read: Power BI Developer Salary

8. Movie Sales Forecasting

The goal of this project is to create an interactive visual experience from a dataset that tracks movie sales over time. You can utilize the 2006–2016 IMDb dataset, which is accessible on both IMDb and Kaggle. The dataset comprises different variables like Budget, Gross, Genre, and Scores as well as a list of films with an IMDb score of 6 or above.

This would show the selected set’s metrics like Average Score and Gross Collections. Plotting a histogram of the score variable with year and genre as slicers can show the frequency distribution of the IMDb scores.

9. E-Commerce Conversion Funnel

Work on this project to create a funnel analysis dashboard to track user interactions on e-commerce websites and optimize the conversion process. Use an e-commerce dataset from Kaggle to begin. You will find data like landing page visits, user actions, timestamps, completed purchases, etc. 

You can track user sessions, calculate conversion rates, categorize user actions, and identify points of drop-offs and factors behind abandoned carts. Use bar graphs or funnel charts for visualization and suggest strategies to optimize conversion rates accordingly.

10. Social Media Engagement Dashboard

The objective of this project is to create a dashboard that tracks and visualizes social media engagement metrics across platforms. Use Kaggle’s social media engagement dataset that includes key metrics, such as comments, likes, shares, and followers. 

Use Power Query and DAX to aggregate data from various platforms and calculate engagement rates. You can integrate external APIs for real-time data. You can also use Power BI’s visualization elements like bar charts, heat maps, and line charts to identify the popular content type, top engagement periods, and effectiveness of different social media strategies.

Advanced-Level Power BI Projects

Here is a list of some of the top Power BI developer projects for experts who are looking for challenging datasets to work on.

11. Investigation of Covid-19 Insights

One of the most well-liked Power BI projects is the COVID-19 insights analysis. It intends to provide a comprehensive summary of the key elements of the COVID-19 epidemic, the current condition, and complete country-level assessments.

A dashboard that provides useful data on cases (active, died, or recovered), death rates, and recovery rates by country and time frame can be made. A full examination of each report page and a management summary of the most significant KPIs may also be included in the dashboard.

For this project concept, consult the COVID-19 dataset available on Kaggle. As for the Power BI data visualization tools, you can use the following:

• Doughnut charts for category-wise case analysis.
• Bar charts for the overview page.
• Point maps, line charts, and column charts.

12. Energy Trade Analysis Worldwide

The analysis of global energy trade is among the most original concepts for Power BI initiatives. This project’s concept covers a range of issues related to the production and exchange of energy worldwide. It discusses a variety of subjects, including the development of wind energy and the use of energy to compare the economies of different countries.

Use the Kaggle dataset of global energy statistics for this project. The dashboard could include the following data: 

• Consumption of primary and secondary energy
• Conventional and non-conventional energy sources
• Renewable energy sources

Power BI visualization types include bar charts, flow maps, cards for the overview page, ribbon charts, treemaps, and bar charts for energy generation. These can all be used for the dashboard.

13. Analysis of Life Expectancy Data

This study evaluates life expectancy statistics based on a variety of factors, such as vaccines, mortality, finances, social factors, and other health-related issues. It will be simpler for a nation to pinpoint the determinant causing a lower life expectancy figure. In this way, a nation can advise on how to increase the life expectancy of its population effectively.

Utilize the WHO’s life expectancy dataset on Kaggle to analyze life expectancy data. The overview page can employ Power BI visualization styles, such as gauge charts, pie charts, line charts, and point maps. The country-specific data can be shown using tornado charts, doughnut charts, treemaps, etc.

14. Global Supply Chain Optimization

This Power BI project aims to analyze the global supply chain process to identify inefficiencies and optimize the process. Choose a dataset with information on suppliers, lead times, inventory levels across supply chains, and transportation routes. Use Power Query to consolidate and preprocess data from multiple sources. Use DAX to calculate several supply chain metrics. Visualize geographic distribution with the help of different charts and point maps. These visualizations will help identify bottlenecks in the supply chain, regions with high shipping costs, and more.

15. Natural Language Processing (NLP) Insights

You can create a project to integrate natural language processing techniques into Power BI and extract insights from textual data sources, such as customer feedback, surveys, and reviews. 

Use datasets containing customer feedback, reviews, and associated metadata. Clean the textual data and use DAX to perform sentiment analysis and visualization. It will help you get information like frequently mentioned keywords, sentiment distribution across products, and areas of improvement.

Why Power BI?

Power BI is one of the best business intelligence (BI) tools in the world for the following reasons:

• Linking to Data Sources : Power BI supports a variety of data sources, making it simpler for users to match data sets from different sources and use them to produce visually appealing reports. It has over 70 connectors that can pull data from Dropbox, OneDrive, CSV, Excel, Azure Data Warehouse, Google Analytics , and other sources.
• High Performance : The Power BI pivot data modeling engine is a columnar database that greatly boosts performance metrics by reducing original data sets from 1 GB to 200 MB.
• Custom Visualization: It offers a wide range of pre-made data visualizations that can be incorporated into interactive reports. The reports can also benefit from custom visualizations created and developed by in-house developers in the Power BI community.
• R Integration for Advanced Analytics: The computer language R offers thousands of packages with a focus on data mining and visualization. Data scientists utilize the programming language R for machine learning , statistical calculation, and complex data modeling. We may import data models developed in R directly into Power BI dashboards and turn them into visualizations.
• Integration with Cortana : Power BI also works with Microsoft’s digital assistant, Cortana. It allows users to use their voice to access dashboard content and ask questions about data. Even by only speaking or typing their searches, users of mobile devices might generate several views.

Through this blog, we’ve learned how important it is to use Power BI in a variety of projects across several sectors to gain practical insights into different sets of information. These real-time Power BI projects will help novice and seasoned data scientists improve their skill sets and understand the integration of business information into data science. 

Out of the ones mentioned in this blog, which Power BI project did you like the best? Share with us in the comments section below. If you are interested in pursuing a career in Power BI, refer to this detailed blog on how to become a Power BI developer and get to know about career scope, salary, and tips.

You can practice the projects on online platforms like ProjectPro, Github, and Kaggle, among others. You can also access pre-built Power BI practice data on the Power BI service website by signing in, choosing the desired workspace, and selecting the data you want to work on.

You may grasp the fundamentals of Power BI within 10 days. However, it will take at least 4 – 6 weeks to understand the tool while dealing with real-time project samples.

Step 1. Structure your project by understanding the objectives and scope, involvement of stakeholders, and gathering all data resources. Step 2. Identify all the requirements of the business intelligence project.  Step 3. Choose a BI platform such as Microsoft Power BI. Step 4. Create a roadmap to implement the Power BI project on the platform – usage scenario, workspace, information protection and security, monitor, and audit of the project.

Yes, you can learn Power BI by yourself with the help of online Power BI course or tutorials.

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Vishakha Bhardwaj is an analytical genius and a Data Science expert. She has worked on numerous projects for the recruitment side of Internshala. She excels at drawing useful insights from data and strategizing revenue goals and user records. A talented professional, she is known for her specialization in Python, SQL, Advanced Excel, Google Analytics, and Metabase.

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17 Best Power BI Projects for Beginner Practice! (2023)

Are you just getting started with Power BI and looking for some project ideas to practice?

In this blog post, we will discuss the top 17 power BI project ideas you should try! For each of the ideas, we will provide an explanation and who should undertake the project.

By the end of this post, you will have a good understanding of what power BI projects you can work on to improve your skills!

Let’s have a look!

What Are The Best Power BI Projects for Beginners?

Read on to find out more details about each of these Power BI project ideas!

1. Online Retail Dashboard

First up in our list of the best Power BI project ideas involves tracking retail sales from E-commerce data.

This power BI project is ideal for those interested in learning data analysis, as it requires leveraging a large dataset to analyze customer behavior and sales trends.

The dashboard can include all the key metrics related to online retail, such as:

• product sales volume
• return/retention rate
• conversion rate

I’d recommend fully utilizing all the features within Microsoft Power BI Desktop, which is free for all Windows computers. For example, use this project to explore the data structure of your data set using Power BI or experiment with the different data visualizations available.

Who Should Create This Project:

This project is best for people who understand e-commerce, retail, and marketing analytics.

Who Would Use This Dashboard:

This dashboard can be used by e-commerce businesses that want to gain insight into their customers, sales trends, and other metrics related to online retail.

In a real-world setting, a project like this can provide good business intelligence that can be used to make decisions on how to better market products or adjust pricing strategies.

You’ll be able to share your work through Power BI reports on the Power BI Service, an online sharing platform used within an organization.

2. Customer Churn Analysis Project

Customers are the backbone of any business, so understanding them and their behavior is key to success.

This next power BI project idea is ideal for those interested in understanding the customer better and finding ways to improve their experience.

The dashboard should include all key customer metrics, such as:

• demographics
• purchase frequency
• customer lifetime value

This project best suits those working in customer analytics. It’s also suitable for beginners with an interest in customer insights.

This dashboard would be used by product managers who require feedback on how customers use products. This information might also be useful for marketing teams.

3. KPI Monitoring Dashboard

This power BI project is perfect for those who want to learn how to create an interactive dashboard that tracks key performance indicators (KPIs) or key financial indicators.

The dashboard should include all the essential KPIs, such as:

• sales volume
• number of units sold
• conversion rates

You can provide a simple and effective KPI tracking report using the Power BI dashboard feature.

You should limit the number of Power BI visualization types in a KPI dashboard to keep things focused for your users.

This Power BI project best suits most Power BI enthusiasts. It’s also suitable for beginners who want to learn Power BI.

Since you won’t be doing any complex data modeling, most data analytics beginners can try this out!

Different departments would use this dashboard in a business, such as marketing, sales, finance, and operations. It’s also really useful for executives who need an overall view of the organization’s performance.

In my personal work experience, KPI dashboards were mostly used by management for a quick overview. For example, KPI dashboards can be used to analyze regional business growth.

4. Sales Performance Dashboard

This next Power BI project focuses on tracking sales performance and providing insights into how sales are progressing. This sales data analysis project can be used to monitor how each sales rep is performing.

The dashboard should include raw business data such as:

• sales volume by product/customer segment
• revenue growth rate
• number of units sold per month

This project is best suited for power BI users with an understanding of sales data analysis. For those who enjoy creating interactive reports, this idea is also for you.

Sales executives and managers would greatly benefit from a project like this. Product teams can also use it to understand the impact of new product launches on sales performance.

5. Financial Dashboard

Finance projects are also an ideal option for Power BI projects because they can complement and improve traditional financial reporting methods.

The power BI dashboard should be able to track key financial metrics, such as:

• profit and loss
• account receivable aging

All businesses require some form of financial analysis. Therefore, a project on financial reports would be highly sought after by hiring managers.

This project best suits power BI users with interest in exploring financial analysis. This includes investment analysts, accountants, finance managers, and even CFOs.

This dashboard can be used by financial teams to track the company’s performance. It would also be helpful for CFOs and executives who need a quick overview of the organization’s finances.

Power BI dashboards like these should also include visualizations to compare budget vs. actual expenditure and revenue. This comparison helps quickly spot any deviations in performance.

This project idea is excellent for learning power BI data visualization. It’s also a good starting point for beginners who want to get acquainted with Power BI in the financial domain.

Ideally, such dashboards should be put into mobile-friendly formats, so they can be compatible with Power BI mobile applications. This will allow CFOs to view their critical financial reports on the go.

6. Customer Segmentation Dashboard

This power BI project is ideal for those who want to learn how to use power BI visuals and features to create customer segments.

The power BI dashboard should be able to track customer segments, such as:

• geographic location
• purchase behavior

For segmentation, you might want to try out clustering visualizations to aid in better understanding.

This project is best suited for power BI users with an understanding of customer segmentation and an interest in marketing analytics.

It’s also suitable for power BI beginners who want to explore the capabilities of Power BI visuals through customer segmentation clustering.

Aspiring data scientists and business intelligence analysts can also work on such Power BI projects since they involve some data science.

Marketing teams can use this dashboard to understand customers better. It would also be helpful for product managers who need to identify different customer segments and target them with specific campaigns.

7. Social Media Analytics Dashboard

A social media analytics dashboard is the perfect way to track how your organization’s social media accounts are performing. This makes for a good Power BI project idea too!

For example, you will likely need to learn how to load a social media marketing analytics dataset to your Power BI Desktop application.

You’ll also need to learn how to filter out irrelevant data from all the noise on social media platforms.

Your Power BI dashboard should be able to track metrics such as:

• engagement rate
• number of followers/subscribers
• number of comments and likes

You can get datasets from these platforms:

Social media marketers or beginners who want a unique project should try this out.

Social media managers can use this dashboard to constantly track their organization’s social media channels for social listening. It would also be helpful for content marketers who want to understand the success of their campaigns.

8. Sales Funnel Report

Sales funnel reports are vital for any company looking to maximize its sales. Go ahead and try creating a project like this if you’re interested in sales analysis.

A Power BI report should be able to track the different stages of a sales process, such as:

• leads generated
• conversion rate from lead to customer
• average revenue per sale

This project is ideal for most beginners. Sales reps can also do a simple project as well.

Sales teams would benefit from such a power BI dashboard, as it allows them to track their performance and better understand the sales process. It would also be helpful for business owners and marketers who want to track their sales funnel performance.

9. Inventory Management Dashboard

Inventory management is essential in any organization, so why not create a power BI project to help power your inventory tracking?

Your power BI dashboard should be able to track key metrics such as:

• inventory levels
• inventory turnover rate

This power BI project is best suited for power BI beginners and those with some experience in inventory management. A data analytics project like this will help gain some relevant background in the logistics field.

Business owners and operations managers would benefit from such a power BI dashboard, as it allows them to track their inventory performance.

It would help warehouse managers manage the day-to-day operations of their warehouses.

10. Manufacturing Analytics Dashboard

Manufacturing analytics dashboards can provide insights into how a manufacturing plant performs and what changes could improve its performance.

These power BI projects should be able to track key metrics such as:

• cost of production
• production efficiency
• number of products produced

Anyone with interest in manufacturing efficiency. Manufacturing engineers and plant managers can work on projects like these. Although not the simplest to understand, beginners can also try this project for a unique dashboard.

Manufacturing teams, business owners, and operations managers.

It would also be helpful for quality control teams to ensure that products are made as per specifications.

11. Budget Forecasting Dashboard

Creating a power BI budget forecasting dashboard is another great project idea that many can benefit from. The Power BI dashboards created can help track and manage the budget for any organization.

• total revenue
• cost of goods sold (COGS)
• research & development costs
• gross margin

Financial planning and analysis managers.

This dashboard is essential for business owners, finance teams, and anyone who needs to track their budget performance.

Financial analysts could also use such Power BI dashboards to forecast future budgets and plan accordingly.

12. Stock Market Visualization and Analysis

This power BI project is a great way to learn Power BI Desktop, analyze stocks, and visualize stock market data. Through the use of Power BI, you can explore the nature of stock data and their data models.

Your power BI dashboard should include the following:

• stock prices
• market capitalization
• volume of trading

Anyone interested in tracking the stock market. Experienced power BI users can create more detailed Power BI projects related to stocks as well.

Traders and investors, business owners, market analysts, and finance teams.

13. Web Traffic Analysis and Visualization

For businesses that rely on their website for marketing and sales, having a Power BI dashboard to track web traffic trends can provide invaluable insights.

Power BI projects like these are simple use cases where raw business data is used for data analytics and business intelligence .

This project will teach you how to connect integrations from Power BI Desktop to Google Analytics.

• number of visitors
• bounce rates

14. HR Analytics and Visualization

HR business departments need power BI projects that help them understand employee performance, team performance, and other important metrics.

Power BI projects like these can help track key metrics such as:

• employee retention
• turnover rate
• time to hire
• diversity of the workforce

In this project, you can consider doing a statistical analysis to measure turnover rate, and presenting it in an index on your dashboard.

15. Healthcare Analytics Dashboard

Analyzing healthcare data is another interesting project, as it helps medical teams make more informed decisions. You can analyze life expectancy data, electronic health records, and hospital operations data.

Your dashboard should include the following:

• patient satisfaction ratings
• hospital readmissions
• cost of care per patient
• length of hospital stay

If you’re looking to do a deeper analysis of the entire healthcare industry, you can consider doing a global health expenditure analysis. You should also get data from the Global Health Expenditure Database. Access their data here .

Another common dashboard you can consider doing that’s related to the healthcare industry is a COVID insight analysis project. You can use the many databases available online in Kaggle to create a simple cases tracker.

16. Geospatial Data Visualization and Analysis

Geospatial Power BI projects can help visualize data with a geographical component, such as population density and climate trends.

This means that you’ll have to learn more advanced features for overlaying your data onto map layers. Since geospatial data is more complicated, you might need to process your data to uncover underlying data structures before creating any charts.

Your Power BI report should include the following:

• geographical coordinates

17. Project Management Analytics Dashboard

Project managers and executives need power BI projects to track key performance metrics. You can consider starting a simple that can give an overview of the progress of a company-wide project.

• costs per project
• time between milestones
• quality of deliverables
• total number of projects completed successfully

18. Email Marketing Campaign Insights Analysis

This power BI dashboard will track the performance of email campaigns by measuring opens and clicks per campaign and customer engagement.

You’ll likely need to connect your email client with Power BI desktop to access your data.

If you’re looking for power BI projects to learn how to connect integrations from Power BI Desktop, then you can consider this power BI project.

Your power BI report should include the following:

• number of emails sent
• number of opens
• number of clicks
• customer engagement rate

I would say that this is a beginner-level Power BI project, since not much cleaning would be require before crafting a dashboard.

Related Questions

How long does it take to complete a power bi project.

Power BI projects can take a few hours to several weeks or even months. The amount of time needed to complete a power BI project will depend on the project’s complexity and the user’s skillset. Generally, power BI projects can take anywhere from a few hours to several weeks or even months.

What is Power BI mostly used for?

Power BI is mainly used for creating visually appealing data analyses and visualizations. It’s a powerful business analytics tool that can be used to develop reports, dashboards, and other insights.

Power BI can also analyze large data sets, create predictive models, and automate processes. Additionally, Power BI is often used to track key performance indicators (KPIs) and build data-driven decisions.

Is Power BI easier than Python?

Power BI is a powerful business intelligence tool that is easier to learn than Python. However, Power BI does come with a learning curve and requires knowledge of SQL queries and other data manipulation techniques.

On the other hand, Python is a more flexible tool that can be used for various tasks, including data visualization, web development, and data cleaning.

Can Power BI learn in 2 days?

Although it is possible to learn the basics of power BI in 2 days, it may take longer to become an expert power BI user. It is important to understand that power BI projects require knowledge of SQL queries and data manipulation techniques. Therefore, learning power BI will require practice and dedication.

Final Thoughts

That’s all the Power BI project examples I have!

If you want to become an expert power BI user, then these projects will provide the perfect starting point.

I hope these ideas inspire you to create beautiful, comprehensive dashboards.

Thanks for reading!

I'm a tech nerd, data analyst, and data scientist hungry to learn new skills, tools, and software. I love sharing content with my years of experience in data science, marketing, and tech startups.

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Table of content

Why power bi, power bi project ideas, power bi projects for beginners, power bi real-time projects.

In Business Intelligence , Power BI is a suite of various Business Intelligence tools and techniques designed to analyze raw business data and convert that into actionable insights. These tools include Power BI Desktop, Power BI service, Power BI apps, and more.

Developed by Microsoft, Power BI offers BI capabilities with such a simple interface that even a non-technical users can create interactive dashboards on their own. There are hundreds of data visualizations that a user can apply to different data sets and create visually interactive dashboards.

Check out this YouTube video to learn more about Power BI:

The following are the reasons why Power BI is considered to be one of the best business intelligence tools in the world:

Easy to connect with data sources

Power BI supports a myriad of data sources that make it easier for a user to align data sets from different sources and use them to create compelling reports. It has 70+ connectors that can be used to extract data from sources such as Azure Data Warehouse, Google Analytics , OneDrive, Dropbox, Excel, CSV, and SQL databases.

High performance

The pivot data modeling engine is a columnar database in Power BI that significantly compresses the size of original data sets from around 1GB to 200 MB, improving the performance metrics.

Custom visualization

Power BI comes with a ton of predesigned data visualizations that can be leveraged to create interactive reports. However, we can also give the reports an extra touch by adding custom visualizations created and shared by in-house developers on the Power BI community.

Check out our Power BI Training Course in India !

Advanced analytics with R integration

R, the programming language, features thousands of packages dedicated to data mining and visualization. Data scientists use R for complex data modeling, machine learning, and statistical computing.

Power BI allows us to directly import data models created in R to the dashboards and convert them into visualizations.

Cortana integration

Power BI also supports Microsoft’s digital assistant Cortana, which enables a user to verbally ask questions about the data and access the dashboard content. Mobile users can even create different views by simply speaking or typing their queries.

Now, let us have a look at some examples of Power BI projects that you can create and add to your portfolio. You can also use these projects to practice and get hands-on experience of the various tools used for data visualization.

Check out these Interview Questions For Power BI and prepare yourself for a Business Analyst job interview.

Although every project requires different data sets and a new approach, you can divide your project workflow into roughly four stages. They are as follows:

Connecting data sources

The first step in any Power BI project is to add raw data from different sources and collect that on a single Power BI interface. The data can be streamed from multiple sources such as Excel spreadsheets, CSV files, local databases, SQL servers, etc.

Data transformation

Once the data is connected to Power BI Desktop, the next step is to transform the data based on the business requirements. In data transformation, we define the relationship between different variables, remove redundancies, add default values, and create new columns through calculated fields.

Data visualization

The third stage is to convert the transformed data into graphical representations such as charts, graphs, maps, etc. Data visualization makes it easier for a user to comprehend complex numbers and use them to make informed decisions. In Power BI, you can create stunning visualizations with simple drag-n-drop features.

Building the dashboard or reports

The last step in your project is to assemble all visualizations on a single interface like tiles. A single page of visualizations is known as a dashboard, while multiple pages are eligible to create a report. These reports and dashboards are now ready to be published and shared with other users via the Power BI service.

Enroll in our Power BI Certification training and start learning Power BI!

Based on your level of expertise in Power BI, we have listed a few Power BI projects that will help you to enhance your knowledge and improve your portfolio. If you are a newbie, then check out the projects for beginners, while the intermediate and advanced users can go through the list of Power BI live projects.

As a beginner, your main focus should be on improving your data analytics and visualization skills and learning how to apply different techniques to make your reports more interesting. For that, we have listed a simple project in Power BI that shows the performance of a company product.

Marketing Campaign Insights Analysis:

A robust marketing campaign is a great way to reach consumers, clients and leads. Your campaign data analysis can provide you with valuable insight into your target audience, marketing channels, and budget. This will provide you with the basic do’s and don’ts of your next campaign. This is where the role of Power BI is invaluable.

This project showcases the efficiency of various marketing campaigns. This project can be used to access the success of marketing campaigns and several other activities carried out under this management. The beginner-level project can be done with the Marketing Analytics dataset which provides deep-insight into the customer’s profile preferences and channel performance. The dataset can be used for EDA, statistical Analysis, and visualizations.

A power Bi dashboard can consist several types of visualizations including bar-charts for category wise expenditure, smart features that highlight the key aspects of the campaign, bubble charts showcasing customer-wise spending.

such as Bar Charts for category-wise expenditures, Smart Narratives for highlighting key aspects of the campaign, Bubble Charts for customer-wise spending, Column Charts for campaign success rates, Cards for highlighting individual insights, etc.

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Financial Performance Analysis

Microsoft Power BI is used for financial analysis to gather and analyze KPIs (Key Financial Indicators), charts, and financial statements. The purpose of this BI project is to optimize financial reporting in a firm that provides accounting services to clients seeking timely delivery of critical financial reports. Through this analysis, you will be able to access reliable financial reports quickly and efficiently. Multi-company financial datasets may be utilized for this project.

Learn a step-by-step guide on exporting Power Bi data to excel from our blog!

The project outlined here can also be applied to the migration of traditional financial reporting from Excel to BI dashboards, allowing customers to track their financial health and productivity more effectively. In this project, Power BI data visualization options can be utilized for three scenarios as given below:

• Funnel charts, combo charts (such as column charts, waterfall charts, line charts) for the summary page or overview page;
• Cards, Funnel Charts, and Combo Charts (such as Line Charts and Column Charts) for the income statement page;
• Cards and Tables for the balance sheet page.

Customer Churn Analysis:

A major challenge that modern enterprises face is customer migration (churn). Churn, or customer attrition, is the act of customers stopping purchasing from a business or interacting with it. What can we do to overcome this challenge? The idea is to know the reasons why customers churn, the factors that impact that, so that appropriate measures can be taken to retain them. This is where Power BI comes into play.

Through this Customer Churn analysis project, one can uncover what causes your customers to stop using your product or service. Business leaders, managers, or analytical users can use this Power BI project to analyze regional business growth and the profit distribution among customers. With the right visualization and data structure, they can receive extensive data. As part of the project, regional cash inflows will be considered, as well as product-specific churn over the course of time. To complete this beginner-friendly project, you will need the customer segmentation dataset. In this project, Power BI data visualization options can be utilized for different scenarios as given below:

• Combo Charts, Bar Charts, Line Chart, Cards, Tables, etc., for overview page.
• Column Charts, Bubble Charts, Point Maps, Tables, etc., for the customer segmentation page.

Sales and product manufacturing:

In this project, we have used a sample data set from Microsoft Power BI and visualized it to show the profit by product, sales, and other key influencers, which may impact the performance of the company.

Do you know What are the differences between Power BI and Tableau !

As discussed earlier, the sample data set has to be connected with Power BI Desktop to filter out irrelevant data, then visualize and export filtered data in the form of dashboards. You can check out the complete process of creating this dashboard in our Power BI dashboard tutorial.

You can use the same data set to create more Power BI sample projects and advanced visualizations.

You can find a lot more sample projects like these and data stories in the Power BI community .

Below are a few more Power BI projects for beginners that you can get from Power BI documentation and practice by yourself:

Do you know What are the differences between MSBI and Power BI !

Sales and Returns:

In this project, the authors have created a report on the sales and returns of a company that sells Microsoft products. By analyzing the report’s content, the company can implement a drill-down approach and the stakeholders can modify their approach to achieve the desired results.

Below is the resulting dashboard that you will get after performing all operations:

IT Spend Analysis :

Organizations keep a record of various resources that they have spent during projects. These records can be analyzed through Power BI and used to effectively manage the resources for upcoming projects and make more profit.

Learn about Power BI Components in our blogs!

Creating a project like IT Spend Analysis, which is already being used, will improve your portfolio. A project like this will leave a positive impression on your resume and let the recruiters know that you have really good knowledge about the problems being faced by an organization.

You can use similar metrics in your dashboard to make it more informative:

Check out our blog on Power BI Tutorial !

Power BI enables a user to connect live data sources to their dashboard. It also helps make on-point decisions through live feedback. These dashboards are very helpful, especially for the situation where you have to make split-second decisions based on the situation.

Although real-time projects look cool and provide live information in the form of visualizations, they also require a lot of skills in data analytics and knowledge of the Power BI server. You can only publish live dashboards if you have access to the Power BI server, which is a paid tool. So, if you have it, then take look at these fancy Power BI projects ideas you can make:

Airport Authority Performance dashboard:

The aviation industry saw huge growth in the number of passengers traveling around the world. Right now, there are more than 5,000 airplanes up in the sky around the world taking passengers or cargo to various destinations. However, maintaining these flights requires a lot of planning and real-time decision-making capabilities.

This is where tools like Power BI come into play; airport authorities use Power BI dashboards to track the number of planes taking off and landing at the airport. Power BI also helps airport authorities to set alerts if something goes wrong.

Thus, you can create these projects and see how Power BI functions in real life.

Check out our Power BI Training Course in London !

Below is an example of a Power BI Airport Authority Performance Dashboard:

Covid Analysis dashboard

As we all know, Covid-19 had a devastating impact on the entire human civilization. The sudden outbreak in all countries forced global leaders to take drastic measures in order to prevent the virus from infecting the larger population.

The Covid Analysis dashboard uses a heat map with a bunch of tables to show the number of Covid-19 cases around the world. It is a great project and makes you aware of the current situation. Below is the screenshot of the Power BI dashboard created for Covid analysis :

Check out if you want to learn How to Create a Power BI Heatmap !

Climate Change dashboard

Climate change is yet another hot topic that grabs global attention after the occurrence of any major disaster, be it hurricanes, flash floods, rising sea levels, forest fires, or a rise in average global temperatures. This dashboard utilizes a variety of tools and data sets to show that climate change is real.

By the end of this project, you will have a better understanding of how two seemingly different data values can affect the entire system and how to find such relationships.

Check out How to Build an impressive Power BI Resume !

So, these are the top Power BI project ideas that you can work on to improve your data analytics and visualization skills. Power BI offers a plethora of tools and features that allow a user to create interactive dashboards and share them over the internet. On Power BI, you can also collaborate with other users and stakeholders to work on separate projects.

Check out our blog on How to Become a Power BI Developer !

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About the Author

As a Data Analyst & Machine Learning Associate, Nishtha uses a combination of her analytical skills and machine learning knowledge to interpret complicated datasets. She is a passionate storyteller who transforms crucial findings into gripping tales that further influence data-driven decision-making in the business frontier.

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Top 7 Power BI Projects for Practice 2024

• December 4, 2023

Stella Martin

Table of Contents

Microsoft Power BI is one of the most used software for professionals who deal with data regularly for multiple purposes. Power BI’s interactive dashboards, exceptional graphs, charts, and various AI-enabled features, are helping users convert raw data into informative visuals and reports. Though the Power BI interface might seem user-friendly, using Power BI projects for practice is quite important in the long term. 

Check Out These Amazing Power BI Projects for Practice

Power bi projects for practice, 1. customer churn analysis.

This refers to the customers’ product sales and profits that data professionals can use to analyze regional business growth across multiple regions to understand valuable insights and distribute profits among customers. With the right visualizations and data structure, analysts can easily receive extensive data. 

Image Source: community.fabric.microsoft.com

2. Marketing Campaign Insights Analysis

Suppose you want to observe and infer how marketing campaigns perform in product groups and platforms. In that case, you can use the Marketing Analytics dataset available on Kaggle for this beginner-level project. This is quite beneficial for professionals aspiring to be marketing managers or looking for career advancement in the marketing department of any organization. Bar Charts for category-wise expenditures, Column Charts for campaign success rate, Smart Narratives for displaying the key highlights of the campaign, Bubble Charts for customer-wise spending, Cards for showing individual data insights, etc. are the major significant things that can be used in this Power BI project for practice. 

Image Source: blog.enterprisedna.co

3. HR Analytics in Power BI

Atlas Labs is one of the best fictitious software for HR data, and you can use it to practice HR Analytics in Power BI. If you’re aspiring to be an HR professional who takes care of various employee metrics, HR Analytics in Power BI for beginners is quite essential. You’ll have a holistic view of employee metrics, and you can also evaluate employee performance and attrition. 

Image Source: datacamp.com

4. Inventory Management and Analysis

Power BI for Inventory Management allows project managers and inventory managers to check inventory status. It is extremely crucial for professionals who are in organizations that sell a range of products across different warehouses. Inventory management is not only about cash in-flow or out-flow but also about checking stocks and determining if that will be enough to meet the ongoing requirement.

5. Healthcare Data Analysis

Using Microsoft Power BI projects for healthcare practices, you can use a fictional consulting company called HealthStat, but you’ll get a real-time dataset. The main agenda of this project is to check hospital efficiency insights and suggest needful recommendations for change. First, you’ll take a close look at the data to get an initial understanding. After that, you’ll dig deeper into hospitals that stand out in terms of performance. The goal is to figure out the main factors that affect how long patients stay in the hospital and the cost of discharging each patient.

6. Abnormal Credit Card Transactions

Abnormal transactions on credit cards have been quite a popular scenario in this era, and this phenomenon is known as anomaly detection in credit card transactions. Using 3 different ways, supervised (for labeled datasets), semi-supervised (for normally trained datasets), and unsupervised (for datasets without any labels), you can use Power BI for Anomaly Detection in Credit Card transactions using Machine Learning. 

Alt text: learn.microsoft.com

7. Airport Authority Data Analysing

Suppose you’re in charge of any airport or looking for a career in that sector. In that case, you can use the Airport Authority Data Analysis Power BI project to present a comprehensive overview of important airport data. You can get multiple data on the project’s dashboard, with critical information, including the total number of flights (incoming and departing), overall flight delays (both arrivals and departures), ground processing time, and feedback from passengers. This analysis could be valuable for airport management authorities in making informed decisions promptly, especially in situations involving flight changes, emergencies, or delays.

Alt text: community.fabric.microsoft.com

Advantages of using Power BI Projects for Practice:

• You can use Power BI projects for practice to create interactive and personalized dashboards and reports that show the most relevant information for your business goals.
• If you want to access real-time data for your practice and refresh it easily, you can always have the latest insights for decision-making using Microsoft Power BI.
• You can integrate Power BI with Excel and other Microsoft apps, as well as a wide range of data sources, such as Azure, SQL Server, SharePoint, and more.
• Power BI now has magnificent AI features and machine learning that you can explore and practice to discover patterns, trends, and insights from your data.
• You can collaborate and share your data and reports with others in your organization or publish them online for a wider audience.

Microsoft Power BI Projects can be, therefore, used to improve your efficiency in dealing with data from various sources. If you’re looking for career advancement, these projects will help you in gaining valuable experience. However, if you’re a beginner, undergoing a Microsoft Power BI Data Analyst PL-300 training will increase the relevance of your resume and stand out from non-certified counterparts. Therefore, if you’re a data professional or looking for a job opportunity in the data world, the PL-300 course with Microsoft Power BI Projects for practice should be one of your topmost priorities. 

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SQLicious/Microsoft-Power-BI-Data-Analyst-Professional-Certificate-Exercises

Folders and files, repository files navigation, microsoft power bi data analyst professional certificate repository.

This repository highlights my progress in the Microsoft Power BI Data Analyst Professional Certificate program, designed to impart critical business intelligence skills necessary for excelling as a Power BI analyst in less than five months.

Philosophy for Taking the Course

As a data engineer proficient in the Azure stack, expanding my skills within the Microsoft ecosystem was a strategic move. Already certified in Tableau, I identified the value of mastering Power BI to gain a competitive edge in organizations that favor the Azure-Microsoft stack for their BI tools. This realization motivated me to delve into the Power BI specialization.

Achievements and PL-300 Certification

Initiated in December 2023 with a two-month completion target, this intensive Power BI program involved me deeply in all its aspects—exercises, quizzes, practice tests, and dashboard creation to bolster my portfolio. This effort has enhanced my business intelligence capabilities, establishing me as a well-rounded data professional, poised for opportunities in any data-centric organization.

Specialization Outcome

• Professional-level training from Microsoft.
• Portfolio-ready projects demonstrating proficiency.
• An employer-recognized certificate from Microsoft.
• Qualification for in-demand job titles: Business Intelligence Engineer, Data Analyst and Power BI Analyst.

Discount Available

For details on available discounts for this course, please refer to the official course page .

Course Modules

Click on the links for each course below to access the solution files for exercises completed within that specific course

Course 1: Preparing Data for Analysis with Microsoft Excel

• Duration: 18 hours
• Rating: 4.7/5 (1,091 ratings)

Course 2: Harnessing the Power of Data with Power BI

• Duration: 16 hours

Course 3: Extract, Transform and Load Data in Power BI

• Duration: 20 hours

Course 4: Data Modeling in Power BI

• Duration: 26 hours

Course 5: Data Analysis and Visualization with Power BI

• Duration: 29 hours
• Completed 20 Quizzes and 7 graded assignments

In this course, I learned how to:

• Design and format reports and dashboards with Power BI visuals
• Navigate and export reports and dashboards
• Perform advanced analytics with Power BI
• Undertstand the AI visuals in Power BI and when to use them

Course 6: Creative Designing in Power BI

Course 7: deploy and maintain power bi assets and capstone project.

• Duration: 25 hours
• Rating: 4.0/5 (25 ratings)

Course 8: Microsoft PL-300 Exam Preparation and Practice

• Duration: 36 hours

Week2 Activities and Exercises completed

• 1: Learn to configure and format table/column properties in Power BI Desktop for improved data model clarity and accurate insights.
• 2: Create a common date table in Power BI to enhance your data analysis and visualization by effectively managing time-related data.
• 3: Disable the automatic summarization of sales in Adventure Works and create an explicit measure using DAX or Power BI’s quick measures.
• 4: Create Semi-additive measures in Power BI Desktop
• 5: Apply DAX knowledge in Power BI to add a calculated table to a dataset.
• 6: Creating a reporting Hierarchy
• 7: Implement index columns in Power Query to structure datasets and enhance DAX query efficiency in Power BI.
• 8: Optimize the Adventure Works dataset in Power BI by refining data types, pruning rows/columns, and enhancing relationships to boost model performance.

Week3 Activities and Exercises completed

• 1: Apply visualization techniques in Power BI to format and configure visualizations effectively.
• 2: Enhance visualization appearance with conditional formatting in Power BI.
• 3: Upgrade report appearance and functionality by adjusting page settings in Power BI. Hands on activities 1- 3 were combined in one file "Wk3_Sales-Categorical-Analysis"
• Incorporate engaging custom visuals into Power BI reports for enhanced interactivity.
• Utilize the Play Axis visualization in Power BI for dynamic time series analysis.
• Streamline report aesthetics and consistency by exporting and importing themes in Power BI.
• Enhance report interactivity and navigation using bookmarks in Power BI.
• Enhance interactivity with custom tooltips in Power BI for detailed data insights.
• Reorganize data using advanced sorting techniques in Power BI for clearer insights.
• Enable intuitive data queries with the Q&A feature in Power BI for user-friendly analytics.
• Incorporate the Q&A feature into Power BI dashboards for easy, natural language visualization creation.
• Utilize anomaly detection in Power BI to identify and analyze unusual data patterns.
• Apply grouping in Power BI to segment data for clearer analysis and reporting.
• Analyze sales data with Power BI's Analyze feature to identify trends and contributing factors.

Week4 Activities and Exercises completed

Repository structure.

Each folder in this repository corresponds to a course in the specialization. Within each folder, you will find my projects, exercises, and notes that reflect my learning and application of the course material.

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