June 18, 2024

10 Great Business Analyst Projects for Your Portfolio (2024)

If you're serious about launching a career as a business analyst, you'll need more than just certificates and an impressive resume. To stand out in a competitive job market, you need to showcase your skills through a portfolio of relevant business analyst projects. Building a project portfolio is essential for two key reasons:

  1. Practice makes perfect: Completing end-to-end business analyst projects allows you to apply your skills to solve real-world challenges. While exercises and case studies are helpful, hands-on projects provide the depth of experience that employers value. Project-based learning offers an effective approach for aspiring business analysts to gain practical, job-ready skills by bridging the gap between theory and practice.
  2. Prove your capabilities: When you're applying for business analyst roles, a strong portfolio is your secret weapon. It demonstrates your ability to tackle complex problems, collaborate with stakeholders, and deliver impactful solutions. A portfolio of hands-on projects is essential for aspiring business analysts to land a job by demonstrating their ability to apply skills to real-world problems, particularly when they have no experience.

Business Analyst deeply immersed in data analysis, unlocking business insights.

What to expect: Before we get into any specific project details, we'll first take a look at how you should approach selecting the right projects for you portfolio. Next, we'll go over the skills and knowledge you'll need to get started. Finally, we'll list 10 business analyst projects that we know will give your portfolio a real boost.

Choosing the right business analyst projects for your portfolio

With so many potential projects to choose from, it can be challenging to know where to start. To help you navigate this process, let's take a look at some key factors to consider when selecting business analyst projects for your portfolio.

  • Skill level and learning goals: If you're just starting out, focus on projects that allow you to develop foundational skills such as data cleaning, data analysis, and documenting insights. As you gain more experience, you can gradually take on more complex projects that challenge you to apply advanced techniques and methodologies.
  • Personal interests and passions: Selecting projects that align with your personal interests and passions can help you stay motivated and engaged throughout the learning process. For example, if you're passionate about sustainability, you might choose projects that focus on improving environmental performance or reducing waste in business processes. By working on projects that excite you, you'll be more likely to invest the time and effort needed to produce high-quality deliverables.
  • In-demand skills and industry trends: To maximize the impact of your portfolio, it's important to choose projects that showcase in-demand skills and align with current industry trends. Research job postings and industry reports to identify the skills and competencies that employers are looking for in business analysts. For instance, with the growing importance of data-driven decision making, projects that demonstrate your ability to analyze and visualize data using tools like Tableau or Power BI can help you stand out to potential employers.

Step-by-step guide

Now that we've explored some key factors to consider, let's walk through the process of selecting the right business analyst projects for your portfolio:

  1. Assess your current skill level and identify any areas for improvement
  2. Set clear learning goals and objectives for your project-based learning journey
  3. Select project ideas that align with your interests, passions, and learning goals
  4. Research industry trends and in-demand skills to refine your selection
  5. Evaluate potential projects based on factors such as scope, complexity, and required resources
  6. Select projects that offer the best opportunities for skill development and portfolio impact
  7. Plan your projects carefully, setting clear milestones and deliverables
  8. Execute your projects with a focus on quality, collaboration, and continuous improvement
  9. Seek feedback from mentors, peers, and industry professionals to refine your work
  10. Showcase your completed projects in your portfolio, highlighting the skills and value you bring to the table

Remember, the most effective way to learn is by doing, so don't be afraid to dive in and start tackling real-world business challenges today!

Getting started with business analyst projects

Ready to get your feet wet with business analysis projects? You'll need a mix of technical skills, business know-how, and people skills. But don't worry, you can build up these abilities through hands-on practice.

To get the ball rolling on a project, focus on nailing these key deliverables:

  • Use cases
  • Process flows
  • Requirements documents

These will help you pin down the project scope and get everyone on the same page. Crafting solid versions of these docs is a core skill for business analysts.

Additional key tools:

* - While Python is more commonly associated with data analysts and data scientists due to its powerful data manipulation and analysis capabilities, business analysts are increasingly using Python for more advanced data analysis tasks. Python's ability to handle large datasets, automate repetitive tasks, and perform complex analyses makes it a valuable skill for business analysts looking to enhance their technical capabilities. Having Python skills is great way to set yourself apart from others applying for the same business analyst role.

When you're ready to tackle a project, knock out these first steps:

  1. Whip up a business requirements document (BRD) and project vision to get the team aligned.
  2. Get your tech environment set up with the right software for the job.
  3. Deploy the application for testing and production.

Remember, you don't have to take on the world right away. Start small and gradually level up your skills. Focus on simpler tasks at first, then work your way up to more complex challenges. This lets you grow your abilities while getting real project experience under your belt. This article has more tips on setting up your project environment. With some practice and persistence, you'll be tackling ambitious projects like a pro in no time.

Real learner, real results

Take it from Aleksey Korshuk, who leveraged Dataquest's project-based curriculum to gain practical data science skills and build an impressive portfolio of projects:

The general knowledge that Dataquest provides is easily implemented into your projects and used in practice.

Through hands-on projects, Aleksey gained real-world experience solving complex problems and applying his knowledge effectively. He encourages other learners to stay persistent and make time for consistent learning:

I suggest that everyone set a goal, find friends in communities who share your interests, and work together on cool projects. Don't give up halfway!

Aleksey's journey showcases the power of a project-based approach for anyone looking to build their data skills. By building practical projects and collaborating with others, you can develop in-demand skills and accomplish your goals, just like Aleksey did with Dataquest.

10 Business Analysis Project Ideas

The following ten project ideas provide an excellent introduction to essential business analysis techniques for beginners. You'll get to:

  • Apply key concepts like data analysis, visualization, and business intelligence to real-world scenarios
  • Develop a strong foundation and portfolio in the field
  1. Profitable App Profiles for the App Store and Google Play Markets
  2. Exploring Hacker News Posts
  3. Clean and Analyze Employee Exit Surveys
  4. Visualization of Life Expectancy and GDP Variation Over Time
  5. Building a BI App
  6. Business Intelligence Plots
  7. Data Presentation
  8. Creating An Efficient Data Analysis Workflow
  9. Identifying Customers Likely to Churn for a Telecommunications Provider
  10. Analyzing Startup Fundraising Deals from Crunchbase

The following sections walk through each project in detail, showing you how to apply your skills to real business challenges and drive smarter decisions. Let's go!

1. Profitable App Profiles for the App Store and Google Play Markets

Overview

In this guided project, you'll take on the role of a junior business analyst at a company that builds ad-supported mobile apps. Your job is to analyze historical data from the Apple App Store and Google Play Store to figure out what kinds of apps attract the most users and generate the most revenue for the company. Using Python and Jupyter Notebook, you'll clean up the data, analyze it to find the most common app categories and characteristics, and provide recommendations to the business on what types of apps they should focus on building to maximize downloads and profits.

Tools and Technologies

  • Python
  • Jupyter Notebook
  • Business analysis

Prerequisites

This is a beginner-level project, but you should be comfortable working with Python Functions and Jupyter Notebook Course:

  • Writing functions with arguments, return statements, and control flow
  • Debugging functions to ensure proper execution
  • Using conditional logic and loops within functions
  • Working with Jupyter Notebook to write and run code

Step-by-Step Instructions

  1. Open and explore the App Store and Google Play datasets
  2. Clean the datasets by removing non-English apps and duplicate entries
  3. Isolate the free apps for further analysis
  4. Determine the most common app genres and their characteristics using frequency tables
  5. Make recommendations on the ideal app profiles to maximize users and revenue

Expected Outcomes

By completing this project, you'll gain practical experience and valuable skills, including:

  • Cleaning real-world data to prepare it for analysis
  • Analyzing app market data to identify trends and success factors
  • Applying data analysis techniques like frequency tables and calculating averages
  • Using data insights to inform business strategy and decision-making
  • Communicating your findings and recommendations to stakeholders

Relevant Links and Resources

Additional Resources

2. Exploring Hacker News Posts

Overview

In this project, you'll get hands-on experience analyzing a real-world dataset from Hacker News, a popular website in the tech community. You'll learn how to use Python, a powerful programming language, to uncover trends and insights that can help drive business decisions. Even if you're new to data analysis, this project will walk you through key skills step-by-step, including cleaning messy data, calculating key metrics, and identifying factors that impact user engagement. By the end, you'll have a strong foundation in data analysis and be ready to apply your skills to your own business data.

Tools and Technologies

  • Python
  • Data cleaning
  • Object-oriented programming
  • Jupyter Notebook

Prerequisites

To get the most out of this project, you should have some foundational Python and data cleaning skills, such as:

  • Employing loops in Python to explore CSV data
  • Utilizing string methods in Python to clean data for analysis
  • Processing dates from strings using the datetime library
  • Formatting dates and times for analysis using strftime

Step-by-Step Instructions

  1. Remove headers from a list of lists
  2. Extract 'Ask HN' and 'Show HN' posts
  3. Calculate the average number of comments for 'Ask HN' and 'Show HN' posts
  4. Find the number of 'Ask HN' posts and average comments by hour created
  5. Sort and print values from a list of lists

Expected Outcomes

After completing this project, you'll have gained practical experience and skills, including:

  • Applying Python string manipulation, OOP, and date handling to real-world data
  • Analyzing trends and patterns in user submissions on Hacker News
  • Identifying factors that contribute to post popularity and engagement
  • Communicating insights derived from data analysis

Relevant Links and Resources

Additional Resources

3. Clean and Analyze Employee Exit Surveys

Overview

In this guided project, you'll get hands-on experience analyzing real employee data to understand why employees leave their jobs. You'll work with exit surveys from two government education departments in Australia. Using Python and Jupyter Notebook, you'll combine messy data from different sources, clean it up to get it ready for analysis, and then look for insights into the most common reasons employees resign. Finally, you'll share your key findings and recommendations with stakeholders. Doing this project will give you practice with the data cleaning, analysis, and communication skills you need as a business analyst to help organizations make data-driven decisions.

Tools and Technologies

  • Python
  • Pandas
  • Data cleaning
  • Jupyter Notebook

Prerequisites

Before starting this project, you should be familiar with:

  • Exploring and analyzing data using pandas
  • Aggregating data with pandas groupby operations
  • Combining datasets using pandas concat and merge functions
  • Manipulating strings and handling missing data in pandas

Step-by-Step Instructions

  1. Load and explore the DETE and TAFE exit survey data
  2. Identify missing values and drop unnecessary columns
  3. Clean and standardize column names across both datasets
  4. Filter the data to only include resignation reasons
  5. Verify data quality and create new columns for analysis
  6. Combine the cleaned datasets into one for further analysis
  7. Analyze the cleaned data to identify trends and insights

Expected Outcomes

By completing this project, you will:

  • Clean real-world, messy HR data to prepare it for analysis
  • Apply core data cleaning techniques in Python and pandas
  • Combine multiple datasets and conduct exploratory analysis
  • Analyze employee exit surveys to understand key drivers of resignations
  • Summarize your findings and share data-driven recommendations

Relevant Links and Resources

Additional Resources

4. Visualization of Life Expectancy and GDP Variation Over Time

Overview

In this project, you'll get to be a business analyst exploring how life expectancy and GDP have changed in different parts of the world over time. You'll use Power BI to create interactive charts and graphs from a dataset called Gapminder. This will let you uncover trends and differences between regions that can provide valuable insights to help make business decisions. You'll go through the full process of importing and preparing the data, making visualizations, and sharing your findings in an engaging dashboard. This is great practice with core business analyst skills in Power BI that you can showcase in your portfolio.

Tools and Technologies

  • Power BI

Prerequisites

To complete this project, you should be able to visualize data in Power BI, such as:

  • Creating basic Power BI visuals
  • Designing accessible report layouts
  • Customizing report themes and visual markers
  • Publishing Power BI reports and dashboards

Step-by-Step Instructions

  1. Import the life expectancy and GDP data into Power BI
  2. Clean and transform the data for analysis
  3. Create interactive scatter plots and stacked column charts
  4. Design an accessible report layout in Power BI
  5. Customize visual markers and themes to enhance insights

Expected Outcomes

By completing this project, you'll gain practical experience and valuable skills, including:

  • Applying data cleaning, transformation, and visualization techniques in Power BI
  • Creating interactive scatter plots and stacked column charts to uncover data insights
  • Developing an engaging dashboard to showcase your data visualization skills
  • Practicing the full life-cycle of Power BI report and dashboard development

Relevant Links and Resources

Additional Resources

5. Building a BI App

Overview

In this hands-on project, you'll get to be a business analyst at Dataquest, an online learning company. You'll use Power BI to look at data about how many students finish each course and how happy they are with the courses. You'll make charts and graphs to find patterns and figure out which courses need improvement. This will help Dataquest's leaders make smart choices about how to make their courses better for students.

Tools and Technologies

  • Power BI

Prerequisites

To successfully complete this project, you should have some foundational skills in Power BI, such as how to manage workspaces and datasets in Power BI:

  • Creating and managing workspaces
  • Importing and updating assets within a workspace
  • Developing dynamic reports using parameters
  • Implementing static and dynamic row-level security

Step-by-Step Instructions

  1. Import and explore the course completion and NPS data, looking for data quality issues
  2. Create a data model relating the fact and dimension tables
  3. Write calculations for key metrics like completion rate and NPS, and validate the results
  4. Design and build visualizations to analyze course performance trends and comparisons

Expected Outcomes

Upon completing this project, you'll have gained valuable skills and experience:

  • Importing, modeling, and analyzing data in Power BI to drive decisions
  • Creating calculated columns and measures to quantify key metrics
  • Designing and building insightful data visualizations to convey trends and comparisons
  • Developing impactful reports and dashboards to summarize findings
  • Sharing data stories and recommending actions via Power BI apps

Relevant Links and Resources

Additional Resources

6. Business Intelligence Plots

Overview

In this beginner-friendly project, you'll get hands-on experience using Tableau to analyze sales data and provide valuable business insights. You'll compare Adventure Works' online and in-store sales, identify top-selling products, and build interactive dashboards to effectively communicate your findings. Along the way, you'll learn key Tableau skills like creating calculated fields, filtering data, and designing dual-axis charts. By the end, you'll have a professional set of visualizations to showcase to leadership and guide data-driven decision making.

Tools and Technologies

  • Tableau

Prerequisites

To successfully complete this project, you should have a solid grasp of data visualization fundamentals in Tableau:

  • Navigating the Tableau interface and distinguishing between dimensions and measures
  • Constructing various foundational chart types in Tableau
  • Developing and interpreting calculated fields to enhance analysis
  • Employing filters to improve visualization interactivity

Step-by-Step Instructions

  1. Compare online vs offline orders using visualizations
  2. Analyze products across channels with scatter plots
  3. Embed visualizations in tooltips for added insight
  4. Summarize findings and identify next steps

Expected Outcomes

Upon completing this project, you'll have gained valuable skills and experience:

  • Practical experience building interactive business intelligence dashboards in Tableau
  • Ability to create calculated fields to conduct tailored analysis
  • Understanding of how to use filters and tooltips to enable data exploration
  • Skill in developing visualizations that surface actionable insights for stakeholders

Relevant Links and Resources

Additional Resources

7. Data Presentation

Overview

In this project, you'll take on the role of a business analyst exploring customer data for a company. Using Tableau, you'll create interactive dashboards to uncover insights about which marketing channels and customer types are driving the most sales. You'll apply data visualization best practices to build professional dashboards that allow users to filter and explore the data. By the end, you'll have a polished data presentation ready to share your findings with business stakeholders to help guide decision making.

Tools and Technologies

  • Tableau

Prerequisites

To successfully complete this project, you should be comfortable sharing insights in Tableau, such as:

  • Building basic charts like bar charts and line graphs in Tableau
  • Employing color, size, trend lines and forecasting to emphasize insights
  • Combining charts, tables, text and images into dashboards
  • Creating interactive dashboards with filters and quick actions

Step-by-Step Instructions

  1. Import and clean the conversion funnel data in Tableau
  2. Build basic charts to visualize key metrics
  3. Create interactive dashboards with filters and actions
  4. Add annotations and highlights to emphasize key insights
  5. Compile a professional dashboard to present findings

Expected Outcomes

Upon completing this project, you'll have gained practical experience and valuable skills, including:

  • Analyzing conversion funnel data to surface actionable insights
  • Visualizing trends and comparisons using Tableau charts and graphs
  • Applying data visualization best practices to create impactful dashboards
  • Adding interactivity to enable exploration of the data
  • Communicating data-driven findings and recommendations to stakeholders

Relevant Links and Resources

Additional Resources

8. Creating An Efficient Data Analysis Workflow

Overview

In this hands-on project, you'll take on the role of a business analyst at a company that sells programming books. Your goal is to analyze sales data and figure out which books are generating the most profit. You'll use key concepts in R like control flow, loops, and functions to develop a streamlined process for cleaning, transforming and analyzing the data. This project will give you valuable practice in preparing data, uncovering insights, and putting together a structured report with your findings and recommendations that will help drive business decisions.

Tools and Technologies

  • R
  • RStudio
  • Business analysis

Prerequisites

To successfully complete this project, you should have the following foundational control flow, iteration, and functions in R skills:

  • Implementing control flow using if-else statements
  • Employing for loops and while loops for iteration
  • Writing custom functions to modularize code
  • Combining control flow, loops, and functions in R

Step-by-Step Instructions

  1. Get acquainted with the provided book sales dataset
  2. Transform and prepare the data for analysis
  3. Analyze the cleaned data to identify top performing titles
  4. Summarize your findings in a structured report
  5. Provide data-driven recommendations to stakeholders

Expected Outcomes

By completing this project, you'll gain practical experience and valuable skills, including:

  • Applying R programming concepts to real-world business analysis
  • Developing an efficient, reproducible business analysis workflow
  • Cleaning and preparing messy data for analysis
  • Analyzing sales data to derive actionable business insights
  • Communicating findings and recommendations to stakeholders

Relevant Links and Resources

Additional Resources

9. Identifying Customers Likely to Churn for a Telecommunications Provider

Overview

In this beginner project, you'll take on the role of a business analyst at a telecommunications company. Your challenge is to analyze customer data in Excel to identify profiles of those likely to leave the company. Keeping customers is crucial for telecom providers, so your insights will help inform efforts to proactively retain them. You'll explore the data, calculate key metrics, use PivotTables to slice the data, and create charts to visualize your findings. This project provides hands-on experience with core Excel skills for making data-driven business decisions that will enhance your business analyst portfolio.

Tools and Technologies

  • Excel

Prerequisites

To complete this project, you should feel comfortable exploring data in Excel:

  • Calculating descriptive statistics in Excel
  • Analyzing data with descriptive statistics
  • Creating PivotTables in Excel to explore and analyze data
  • Visualizing data with histograms and boxplots in Excel

Step-by-Step Instructions

  1. Import the customer dataset into Excel
  2. Calculate descriptive statistics for key metrics
  3. Create PivotTables, histograms, and boxplots to explore data differences
  4. Analyze and identify profiles of likely churners
  5. Compile a report with your data visualizations

Expected Outcomes

By completing this project, you'll gain practical experience and valuable skills, including:

  • Hands-on practice analyzing a real-world customer dataset in Excel
  • Ability to calculate and interpret key statistics to profile churn risks
  • Experience building PivotTables and charts to slice data and uncover insights
  • Skill in translating business analysis findings into an actionable report for stakeholders

Relevant Links and Resources

Additional Resources

10. Analyzing Startup Fundraising Deals from Crunchbase

Overview

In this beginner-level guided project, you'll take on the role of a business analyst to explore and derive insights from a dataset of startup investments from Crunchbase. By applying fundamental data analysis skills using Python and SQL, you'll work with a large real-world dataset to uncover trends in fundraising, identify successful startups, and find the most active investors. This project will introduce you to techniques for handling large datasets, selecting the right tools for analysis, and leveraging SQL databases. You'll build your skills in applying the data analysis process to real business scenarios and communicating insights to stakeholders.

Tools and Technologies

  • Python
  • Pandas
  • SQLite
  • Jupyter Notebook

Prerequisites

Although this is a beginner-level SQL project, you'll need some solid skills in Python and data analysis before taking it on:

Step-by-Step Instructions

  1. Explore the structure and contents of the Crunchbase startup investments dataset
  2. Process the large dataset in chunks and load into an SQLite database
  3. Analyze fundraising rounds data to identify trends and derive insights
  4. Examine the most successful startup verticals based on total funding raised
  5. Identify the most active investors by number of deals and total amount invested

Expected Outcomes

Upon completing this guided project, you'll gain practical skills and experience, including:

  • Applying pandas and SQLite to analyze real-world startup investment data
  • Handling large datasets effectively through chunking and efficient data types
  • Integrating pandas DataFrames with SQL databases for scalable data analysis
  • Deriving actionable insights from fundraising data to understand startup success
  • Building a project for your portfolio showcasing pandas and SQLite skills

Relevant Links and Resources

Additional Resources

How to prepare for a career as a business analyst

Starting your path to becoming a business analyst means knowing what employers are looking for in terms of qualifications, knowledge, and skills. This section will help you navigate that path.

Check out job listings

Begin by browsing current job listings to see what qualifications, knowledge, and skills are in demand. Trusted sites to look for business analyst positions include:

Get ready for success

Here are some steps to help you succeed in your business analyst career:

Showcase your work

Creating a GitHub portfolio of business analyst projects is a great way to show potential employers your problem-solving skills and project management abilities. Include a variety of projects that demonstrate different skills and levels of complexity.

When to start applying

Don’t wait to have every skill listed in job postings before you start applying. Aim for about 70-80% of the required skills, as many employers value potential and the ability to learn on the job. Project-based learning is a practical way to bridge the gap between theory and real-world skills.

By building the right skills, getting relevant certifications, and showcasing your work, you'll be in a great position to land a rewarding job in this field. Remember, every business analyst started somewhere – just keep pushing forward and you'll get there!

Conclusion

If you're aiming to stand out as a business analyst, getting hands-on with real projects is the way to go.

By doing the actual business analysis work, you’ll pick up crucial skills like gathering requirements, managing stakeholders, and visualizing data. Plus, you'll have a solid portfolio to show potential employers, proving you know how to go from theory to practice.

If you’re looking for a structured way to get there, consider our Business Analyst with Power BI and Business Analyst with Tableau career paths. They’ll give you the specific tools and skills you need to succeed.

But if you’re confident in charting your own path, the projects we've shared in this post will definitely help. Keep pushing yourself, take on more challenges, and share your work in the Dataquest community for feedback. The more you practice and apply your knowledge, the more you'll grow.

Business Analyst
microsoft power BI
Tableau
Mike Levy

About the author

Mike Levy

Mike is a life-long learner who is passionate about mathematics, coding, and teaching. When he's not sitting at the keyboard, he can be found in his garden or at a natural hot spring.

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