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This course is part of the Business Analytics Specialization

Business Analytics Capstone

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About this Course

The Business Analytics Capstone Project gives you the opportunity to apply what you've learned about how to make data-driven decisions to a real business challenge faced by global technology companies like Yahoo, Google, and Facebook. At the end of this Capstone, you'll be able to ask the right questions of the data, and know how to use data effectively to address business challenges of your own. You’ll understand how cutting-edge businesses use data to optimize marketing, maximize revenue, make operations efficient, and make hiring and management decisions so that you can apply these strategies to your own company or business. Designed with Yahoo to give you invaluable experience in evaluating and creating data-driven decisions, the Business Analytics Capstone Project provides the chance for you to devise a plan of action for optimizing data itself to provide key insights and analysis, and to describe the interaction between key financial and non-financial indicators. Once you complete your analysis, you'll be better prepared to make better data-driven business decisions of your own.

Skills you will gain


Wharton Teaching Staff


University of Pennsylvania

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.

Syllabus - What you will learn from this course

Module 1: capstone project topic - the problem of adblocking.

The Business Analytics Specialization was designed to help you learn how to think about using data in making big (and small) business decisions. In this Capstone project, you'll be asked to create a strategy for a fictional digital search engine and content provider, GoYaFace, Inc. (often abbreviated as “GYF”). The strategy will be used in responding to the increasing popularity and availability of “adblocking” software, which could have significant negative repercussions for GYF’s business. You are to assume the role of the leader of the Digital Advertising Tactics and Action (“DATA”) Team at GYF, which has been assigned the job of formulating GYF’s strategy in responding to the threat of adblocking. Your task is to develop a strategy that will be recommended to GYF’s senior leadership. Using what you've learned about business analytics, you'll (i) create a detailed problem statement focusing on GYF’s ad-buying customers (Module 2), (ii) develop a strategy (Module 3), (iii) describe the anticipated effects of the strategy (Module 4), and (iv) form a plan for measuring the effects of your strategy (Module 4). You'll then put these four pieces together into a final project (Module 5). First, please read the full description of the project in the “Project Description” link below, and then look at the background information about adblockers and the “GYF Company Profile” link in the content for Module 1. When you are ready to begin the first assignment, please move on to Module 2: Defining the Problem.

Module 2: Defining the Problem

In Module 2, you'll define the problem adblockers poses for GYF. GYF is intended to be a composite of leading internet platform and content providers who derive substantial revenues from mobile advertising like Google, Yahoo, and Facebook, so you should frame your research around the real-world problems these companies have faced and are facing. Defining the problem thoroughly will have a direct impact on how successful your strategy will be received by your peers. The more deeply you consider the effects of adblockers on the companies that buy advertising space from GYF, the more appropriate your overall strategy is likely to be. Please use the resources below to find out more about the problem, and then create your Problem Statement and submit it for peer review below. You can and should draw from all of the Business Analytics Specialization courses, but your Problem Statement should focus on how adblockers might adversely affect GYF’s relationship with the companies that pay GYF to place advertisements on GYF’s mobile applications and content. You should consider the issue of causality in your Problem Statement - we've included some lectures from the underlying courses to refresh you on that topci. And you are strongly encouraged to complete and include a response to Application Exercise 1 (see link below) as part of your Problem Statement.

Module 3: Your Strategy

In Module 3, you will focus on creating your recommended strategy for GYF to address adblockers. Your strategy does not have to be lengthy, but it must be clear, and it must address the problem. (Hint: if you have a clearly defined problem, your strategy is much more likely to be clearly defined as well). You'll be submitting your strategy for peer review, and then also reviewing the work of at least 3 of your peers. It's OK if reviewing the strategies of other learners in this course gives you further ideas for revising your own strategy. One of the primary benefits of peer review is to expand the range of feedback you can get, and we designed this Module around peer review so that you can get as much feedback as possible before moving on to the next phase of the project. You may find the resources and lectures below helpful in formulating your strategy and considering how data can be leveraged and appropriately understood. You are strongly encouraged to complete and include your response to Application Exercise 2 as part of your Strategy.

Module 4: Effects of Your Strategy/Measuring these Effects

Module 4 was designed to give you the opportunity to focus on the effects of your strategy. Effects and Measurement can be often overlooked in strategy development; creating a thoughtful and thorough plan for measuring the effects will improve your final project tremendously. In this part of the project, you will describe two events: what you think will happen and how you will measure it. Look to the courses in the Business Analytics Specialization to see what kind of data companies use to measure effects to create a measurement plan of your own. You are strongly encouraged to complete and include your responses to Application Exercises 3 and 4 as part of your Effects and Measurement components. You may create a scenario (Operations Analytics) to predict some of the intended effects of your strategy, either following the outline of Application Exercise 3, or of your own design. Once you submit your own plan for effects and measurement, please review the work of at least three of your peers. You may find new ideas, or new ways of looking at data and measurement from this exercise. We encourage you to incorporate what you've learned into your final submission!

Module 5: Final Project Submission

In this final Module, you will combine the four revised elements of your presentation (Problem Statement, Strategy, Effects, and Measurement, including any responses to the Application Exercises you've completed) into one presentation and submit it for peer review. You'll then be asked to review the work of at least three of your peers. Once you have gotten feedback on your plan, you may use it as an example of strategic thinking at your current job, or as a work sample when you are applying for a new one. A successful strategic analysis which describes the use of data-driven decision making will make you much more marketable in almost any field. Good luck!


It's the excellent for Business Analytics, this like a test all of knowledge that we have learned for Business Analytics Specialization course and can be sure that we can be put in real.

Great explanation , Accouting Analytics - need to include some more additional details on Accounting basics . Non Accounting people finds this course difficult.

I have some of the knowledge. since I followed with the course given, very valuable knowledge for me too much.

Great course! Very well structured and easy to follow. Videos always went into the subject matter in depth and explained the core concepts.

About the Business Analytics Specialization

This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience. You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop basic data literacy and an analytic mindset that will help you make strategic decisions based on data. In the final Capstone Project, you’ll apply your skills to interpret a real-world data set and make appropriate business strategy recommendations.

Business Analytics

Frequently Asked Questions

When will I have access to the lectures and assignments?

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center .

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M.S. in Business Analytics Capstone

MSBA student smiling presenting chart to group of 4 peers

Gain Real-World Experience and Address Business Challenges

In the Capstone Project for Georgetown McDonough’s M.S. in Business Analytics (MSBA) program, you’ll apply the concepts, methods, and tools learned in the program to a challenging business analytics problem with a local, national, or global organization.

Over the course of two semesters, you’ll work with Georgetown’s faculty advisors and a group of other MSBA students to:

As you move through the Capstone Project, you’ll hone your skills with analytics tools, business functions, computing and technology, and value-based data analytics. Your experience from the Capstone Project will help you to stand out from other applicants as you seek to establish or advance your career.

“Graduates are going to show readiness to use data science in real life. They will be able to add this to their resume, show it to employers, and even use it to start a career. The Capstone Projects will be drawn from real-world problems and may be conducted with both industry and academic partners.” Sudipta Dasmohapatra, MSBA Academic Director and Professor

MSBA Curriculum

The curriculum for Georgetown McDonough’s MSBA program includes a total of 18 courses, and each course lasts seven weeks. Part of the curriculum is a two-course Capstone Project, which will begin mid-residency and end with a final project presentation to a partner company/organization prior to graduation.

Selected Capstone Partner Organizations

We have some great partner organizations for you to work with on your projects. Below are just a few of the groups our students have worked with.

Capstone Project Timeline

Rather than moving toward a prescribed outcome, the Capstone Project and its goals should mimic the workplace by emerging organically from insights based on the data collected. To pace the Capstone Project appropriately, student groups adhere to the following timeline of project milestones.

Project Advisors

The Capstone Project will be overseen by the program leadership including the program manager. Other relevant MSBA and Georgetown faculty experts will serve as project mentors, as needed.

Professor Sudipta Dasmohapatra

Sudipta Dasmohapatra is the academic director of the M.S. in Business Analytics (MSBA) and professor of the practice at the McDonough School of Business. She has worked with numerous industry partners and government and non-profit organizations on a variety of business analytics projects.

She has over 10 years of experience consulting in analytics and data science and served on the advisory boards of two strategic analytics start-up firms— Vertaeon, Inc. based in Atlanta, and Kloutics, Inc., based in Pune, India. She joined the board of the Statistical and Mathematical Sciences Institute (SAMSI), an NSF-funded math and statistics institute, in July 2018 as the associate director of diversity. She holds a Ph.D. from The Pennsylvania State University.

Professor Gregory Lyon

Dr. Lyon is the Assistant Director for the Master of Science in Business Analytics (MSBA) and Assistant Teaching Professor in Business Analytics at the McDonough School of Business. He has served as a data science consultant for projects ranging from survey research to global workforce development to regulatory compliance and has taught programming, analytics, and data science to students of all levels, including graduate students and working professionals. Dr. Lyon also holds multiple certifications in cloud computing and analytics including AWS cloud architecture (SAA-C02) as well specialized AWS cloud certifications in machine learning (MLS-C01) and data analytics (DAS-C01). Prior to Georgetown, he earned his Ph.D. at Rutgers University and was a postdoctoral researcher in data science and survey research at Tufts University.

Capstone Partnership Opportunities

The McDonough School of Business at Georgetown University is always seeking additional partners for the MSBA Capstone Project. The MSBA program accepts proposals each spring for additional Capstone Project partner organizations.

“These Capstone Projects will be conducted with industry, government, or academic partners in any field you can imagine, from healthcare to retail to financial services to education. The Capstone Project teams will consist of student members who will be carefully selected into their teams based on the needs of the project.” Sudipta Dasmohapatra, MSBA Academic Director and Professor

By becoming a partner for an MSBA Capstone Project, your company can provide a real-world learning experience for Georgetown students while working through data-driven solutions to your unique challenges.

Download a PDF  for more details about the benefits of a Capstone Project partnership.

For more information about how organizations can get involved with Georgetown University, visit  https://msb.georgetown.edu/corporate-partnerships/

Contact Our MSBA Team

[email protected] Call Today:  (202) 729-9995

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Master of Science in Business Analytics

Columbia Engineering and Columbia Business School Announce New Master’s Degree in Business Analytics

The new MS in Business Analytics, developed in part by IEOR chair Garud Iyengar (left), equips graduates with a deep understanding of data analytics and its practical applications.

Columbia Engineering  and  Columbia Business School  are pleased to offer a new full-time Master of Science in Business Analytics degree, with a three-semester curriculum designed for those who want to focus on learning the modeling techniques and data science tools that help businesses use data to make better decisions. A key element of the new degree program is a capstone project that provides an intense consulting engagement with clients and their real-world business problems using real data sets. 

Read more about  Columbia Engineering and Columbia Business School Announce New Master’s Degree in Business Analytics

*The Master of Science in Business Analytics program is STEM-certified and eligible for F-1 STEM OPT extension.

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Home > Business > Business Analytics Capstone Projects

Business Analytics Capstone Projects

The University of Montana’s Master’s of Science in Business Analytics prepares graduates for successful careers at the intersection of business, statistics, and computing.

Submittable Off-the-Shelf Plan Analysis by Mary Anderson

Submittable Off-the-Shelf Plan Analysis

Mary Anderson

Search Engine Optimization Reporting Tool by Alexis Campestre

Search Engine Optimization Reporting Tool

Alexis Campestre

Batting Order Analysis in Major League Baseball by AJ Eckmann

Batting Order Analysis in Major League Baseball

Northstar Athletics Item Sales Analysis by Nikki Gabrielsen

Northstar Athletics Item Sales Analysis

Nikki Gabrielsen

Visualizing Agricultural Data to Drive Policy by Jon Gilbert

Visualizing Agricultural Data to Drive Policy

Jon Gilbert

Graduation Rates: What Affects Them? by Brenna Hoffman

Graduation Rates: What Affects Them?

Brenna Hoffman

Graduation rates for undergraduate degrees are low (only 60% after 6 years). To better understand what affects them, an analysis was performed on various institutional characteristics and their relationship with 2019 graduation rates.

Updating Embedded Analytics Through Amazon QuickSight by Chris McLoy

Updating Embedded Analytics Through Amazon QuickSight

Chris McLoy

Credit-bearing Internships at the University of Montana by CJ McWilliams

Credit-bearing Internships at the University of Montana

CJ McWilliams

Small Business Online Sales Analysis by Kristi Moore

Small Business Online Sales Analysis

Kristi Moore

Injection Drugs in Montana by Kathryn Puczkowskyj

Injection Drugs in Montana

Kathryn Puczkowskyj

SpectrUM Discovery: Admissions and Gift Shop Sales Report by Aspara Rodriguez

SpectrUM Discovery: Admissions and Gift Shop Sales Report

Aspara Rodriguez

Analysis to identify any patterns within its admissions and gift shop sales data for the SpectrUM Discovery and subsequent recommendations to determine if there are any areas for improvement.

Snapshot into the Prevalence of Youth Vaping and Tobacco Use by Austin Bankston

Snapshot into the Prevalence of Youth Vaping and Tobacco Use

Austin Bankston

Stock Price Risk Analysis and Forecast by Alistair Bernhard

Stock Price Risk Analysis and Forecast

Alistair Bernhard

Many Americans do not own a stock or have not even thought about creating a financial portfolio. This manual will guide a user to better understand the stock market, how to reduce the risk of their portfolio, and forecast closing stock prices a couple days into the future.

Social Media Engagement for 2020 Presidential Candidates by Jordan McNea

Social Media Engagement for 2020 Presidential Candidates

Jordan McNea

A New Angle on Analytics by Aspen Runkel

A New Angle on Analytics

Aspen Runkel

Scraping for Jobs: An Exploration in Data Engineering & Dashboarding by Michael Schwartz

Scraping for Jobs: An Exploration in Data Engineering & Dashboarding

Michael Schwartz

The Yellowstone River, How Much? by Ross Stokes

The Yellowstone River, How Much?

Ross Stokes

Exploring peak shaving for the University of Montana’s energy demand by Sarah Thompson

Exploring peak shaving for the University of Montana’s energy demand

Sarah Thompson

Analysis of Recidivism for Montana Department of Corrections by Taylor Toepke

Analysis of Recidivism for Montana Department of Corrections

Taylor Toepke

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before you go

Help us keep in touch — it won’t take long, mqm: ba–capstone project, mqm: business analytics capstone project, capping off your program.

Your MQM program culminates with the Capstone project, a 6-week intensive experience in which you team up with 3-4 classmates, and partner with a faculty advisor and an organization to solve a specific business problem using analytics techniques. The Capstone project ensures you use the new tools and skills you have developed in a domain-specific business context--all while navigating the challenges of a real world data environment.

Capstone projects serve businesses of all sizes, from startups to Fortune 100 firms, in all industries – including for-profit and not-for-profit organizations. Each project is specific to one of the four curriculum tracks in your MQM program: Finance, Information Risk Management, Marketing, or Strategy. While your team will work on only one Capstone, organizations may sponsor multiple projects in a term meaning several teams in your cohort may have the opportunity to work with the same organization. While client sponsors do not pay a fee to participate in Capstone, they will first be vetted by your program dean .

While Capstone opportunities vary each year, previous projects include:


Just as in the real world, when requested, your team will perform its work under an organization’s confidentiality agreement. While the nature of the agreement will vary depending on the sponsoring organization, your Capstone project is subject to rules crafted between the firm and the MQM Program. Your faculty also have access to a secure research data infrastructure that will be adapted for the needs of your sponsoring organization to ensure integrity of that firm’s data. Only the members of your team will have access to your project sponsor’s data, and the data will only be shared with you in a manner consistent with your sponsor’s third-party data transfer governance rules. Given sensitivity, Fuqua prefers that sponsors not provide personally identifiable information as part of a project, but regardless - as a student in Capstone you will be bound under whatever confidentiality constraints the sponsoring firm requires.

Working with a client on their real-world problem provides valuable experience to enhance your academic knowledge, and develops your professional competency by learning how to work with a client effectively. As part of your Capstone project you will be assigned an industry liaison who will meet with your team approximately once per week throughout the term. The role of the liaison is to provide your team any needed technical and strategic guidance around your project, and their time is limited - so you will need to shape professional questions for your client and prepare discussion materials for those meetings to use their time most efficiently.

Photo of MQM students at graduation

Lessons from My Capstone Project with the Duke University Baseball Team

Interested in sponsoring.

Project evaluations occur through the fall, while projects themselves are run mid-March through early May. Interested organizations should connect with Dr. Jeremy Petranka .

Start Your First Project

Learn By Doing

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15 Business Analyst Project Ideas and Examples for Practice

Explore business analyst real time projects examples curated for aspiring business analysts that will help them start their professional careers. Last Updated: 22 Feb 2023

Your search for business analyst project examples ends here. This blog contains sample projects for business analyst beginners and professionals. So, continue reading this blog to know more about different business analyst projects ideas.

Business analysts are the demand of the twenty-first century! One can easily affirm this by looking at a report by the U.S. Bureau of Labor Statistics, which has revealed that as of May 2020, the median annual salary received by management analysts is $87,660. The bureau’s report also suggests that we are likely to witness an increase in the jobs of management analysts by 11% between 2019 and 2029. The rate is pretty higher than the average for other occupations. Additionally, the bureau mentioned that there is likely to be intense competition for such jobs because the role offers handsome salaries.


Avocado Machine Learning Project Python for Price Prediction

Last Updated : 2023-01-28 20:57:57

Downloadable solution code | Explanatory videos | Tech Support

The role of a business analyst primarily deals with analysing the growth of a business and suggesting methods to improve the existing strategies. Thus, to play such a crucial, one needs to possess a robust set of skills. Let us discuss a few of these to give you a more clear understanding of the skills required to become a business analyst .

Excellent verbal and written communication.

Communicate with different stakeholders and hold different meetings.

Up-to-date knowledge of new technologies and methodologies.

The capability of learning different business processes.

Ability to layout different ways of improving business growth.

Strong time management skills.

Understanding of various analytical tools and their implementation in revealing insights about the business.

Host different workshops and training sessions.

Knowledge of writing formal reports.

Having motivated you with our introduction of this blog, we now present business analyst sample projects that you can try to test/enhance your skills.

Table of Contents

Business analyst practice projects for beginners, business analyst real-time projects for intermediate professionals, advanced business analyst projects examples , top 15 business analyst project ideas for practice.

business analyst projects

This section has beginner-friendly projects for business analyst roles that newbies in this domain can start with.

ProjectPro Free Projects on Big Data and Data Science

1) Market Basket Analysis  

Have you heard of the Beer-and-diapers story? In 2016, Mark Madsen, a research analyst, asked if there is a correlation between the sales of diapers and beers? It turned out that when a few stores placed beers closer to the diapers section, the beer sales went up. This strategy did not work for all the stores, but for a few, it did. By reflecting on this story, we want you to understand how important it is for a business to analyse the correlation between different purchased products, also called Market Basket Analysis.

Market Basket Analysis

Project Idea: In this project, you will work on a retail store’s data and learn how to realize the association between different products. Additionally, you will learn how to implement Apriori and Fpgrowth algorithms over the given dataset. You will also compare the two algorithms to understand the differences between them.

Source Code: Market basket analysis using apriori and fpgrowth algorithm  

Get FREE Access to   Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization

2) Estimating Retail Prices

For any product-selling business, deciding the price of their product is one of the most crucial decisions to make. And, thus for an aspiring business analyst, it becomes essential to understand what factors influence the decision-making process of product prices.

Project Idea: Mercari is a community-driven electronics-shopping application in Japan. In this project, you will build an automated price recommendation system using Mercari’s dataset to suggest prices to their sellers for different products based on the information collected. You will learn how to use Exploratory Data Analysis (EDA) tools and implement different machine learning algorithms like Neural Networks, Support Vector Machines, and Random Forest in R programming language. If you are specifically looking for business analyst finance planning projects for beginners , this project will be a good start. 

Source Code: Machine learning for Retail Price Recommendation with R

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3) Analyzing Customer Feedback

Collecting feedback from customers has become a norm for most companies. It provides them with the user’s perspective and guides them on what changes they should make to their product to increase its sales. Additionally, if the product reviews are public, potential customers feel motivated to trust the genuineness of the seller.

Project Idea: This project deals with the analysis of reviews of products available on an eCommerce website. You will work on textual data and implement data pre-processing methods like Gibberish Detection, Language Detection, Spelling Correction, and Profanity Detection. You will learn how to use the Random Forest model for ranking different reviews. Furthermore, you will explore the method of extracting sentiments and subjectivity from the reviews.

Source Code: Ecommerce product reviews - Pairwise ranking and sentiment analysis  

Recommended Reading: How to learn NLP from scratch in 2021?

Upskill yourself for your dream job with industry-level big data projects with source code

4) Predicting Avocado Prices

Did you know that more than 3 million new photos of avocado toasts were uploaded to Instagram every day in 2107? As per the British Vogue Magazine , this is indeed true. No doubt that so many of us enjoy avocado toasts in our breakfast. If you are also one of such people, this project idea will keep you hooked as it is all about avocados.

Predicting Avocado Prices

Project Idea: In this project, you will learn how a business analyst can use data analysis methods and help promote the growth of a business. You will work on the dataset of a Mexican-based company and layout an Avocado-price-map for them as they plan to expand their reach to different regions in the US. You will be testing the implementation of various models like the Adaboost Regressor, ARIMA time series model, and Facebook Prophet model to predict the Avocado prices.

Source Code: Avocado Price Prediction

5) Predicting the Fate of a Loan Application

Those interested in banking projects for business analysts will indeed consider this one their favorite from this section as this project deals with loans. For understanding banks’ business model, it is crucial to learn the whole process of approving a loan application.

Predicting the Fate of a Loan Application

Project Idea: In this project, you will explore the different factors that influence the eligibility of a loan application’s approval. You will utilise different machine learning algorithms for predicting the chances of success of a loan application. This project will also help you learn about various statistical metrics used widely by business analysts like ROC curve, Gradient boosting, MCC Scorer, Synthetic Minority Over-sampling Technique, and XGBoost.

Source Code: Loan Eligibility Prediction 

Get More Practice,  More   Big Data and Analytics Projects , and More guidance.Fast-Track Your Career Transition with ProjectPro

6) Predicting Customer Churn Rate

When customers start declining at an unexpected rate, various stakeholders go to business analysts for guidance. It is indeed one of the critical responsibilities of a business analyst to check the rate of customers churning out.

Project Idea: This project will guide you about performing univariate and bivariate analysis on the given dataset of a bank. You will learn how different statistical methods like SHAP (SHapley Additive exPlanations), RandomSearch, GridSearch, etc. should be used and interpreted. This project is another instance of a banking project for business analysts . So, if that’s your bias in sample business analysis projects , do check this one out. Source Code: Customer Churn Prediction

Recommended Reading: 

After you have completely solved the above-mentioned projects, proceed to the sample business analyst projects listed in this section to further enhance your skills. These projects are slightly more challenging as they are closer to real-world problems. So, please refer to the source code links for help.

Explore SQL Database Projects to Add them to Your Data Engineer Resume.

7) Prediction of Selling Price for different Products

You must have noticed a few brands sometimes send their loyal customers' coupon codes to attract them. These coupons are often customized according to their purchase history with the brand and thus the offer varies from customer to customer.

Project Idea: In this project, you will work on the dataset of a retail company to estimate the price at which a customer is likely to buy a specific product. Once that is complete, you will use your estimation to design offers for different customers. For the solution, you will use machine learning algorithms like Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks and use different metrics to test each of their performances.

You can add this project under the heading of business analyst finance projects on your resume to highlight the diversity of your skillset.

Source Code : Predict purchase amount of customers against various products

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8) Store Sales Prediction

In most firms, investors are usually external stakeholders that are not directly involved in the firm’s business but are definitely affected by it. And, it is the business analyst’s responsibility to keep the investors up-to-date with the existing and expected growth of the firm’s business model.

Store Sales Prediction

Project Idea: In this project, you will work on the dataset of 45 stores of the famous Walmart store chain. The goal is to predict the sales and revenue of different stores based on historical data. You will work with numeric and categorical feature variables and perform univariate & bivariate analysis to find the redundancy in variables. Additionally, you will learn the implementation of the ARIMA time series model and other machine learning models.

Source Code: Walmart Store Sales Forecasting

9) Analyzing Customer Churn

 It's the customer who pays the wages. --Henry Ford

Customer churn is painful for all the stakeholders in a company. A business analyst must thus look for ways in which the customer churn rate can be minimised. Additionally, they have to identify the cause behind customer churn to improving business growth. Having a fair idea of which customer is likely to churn out will help a business analyst develop better strategies.

Analyzing Customer Churn

Project Idea: In this project, you will be introduced to one of the popular classification machine learning algorithms , logistic regression. The goal is to use logistic regression for estimating the chances of churn for each customer. Through this project, you will get to explore different statistical methods, including confusion metric, recall, accuracy, precision, f1-score, AUC, and ROC.

Source Code: Churn Analysis for Streaming App using Logistic Regression

10) Estimating Future Inventory Demand

While inventory management does not directly fall in the bucket of a business analyst’s responsibilities, one may still find it there as inventory demand directly impacts several other aspects of a business including sales, marketing, finance, etc. With so many advancements taking place in the IT industry, a business analyst can easily use various tools to forecast the inventory demand. Project Idea: Through this project, you will explore the application of various machine learning models, including Bagging, Boosting, XGBoost, GBM, light GBM, and SVM for predicting the inventory demand of a bakery. This project will also introduce you to the implementation of autoML/H 2 0 and LSTM models.

Source Code: Inventory Demand Forecasting using Machine Learning in R

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11) Predicting Coupon Sales

In the previous section, we mentioned a project that will help you in creating customised coupons for a business’s customers. The next step will be to keep track of which coupons have been purchased. This will further help in understanding customer behaviour and preferences.

Project Idea: In this project, you will work on the dataset of one of Japan’s famous joint coupon websites, Recruit Ponpare. The goal is to estimate which coupons a customer is likely to buy based on their previous purchases and browsing behaviour on the website. You will use different graphical methods to visualise the data and various methods of handling missing values in a dataset. You will evaluate the cosine similarities of coupons and users and use them to make the desired predictions.

Source Code: Build a Coupon Purchase Prediction Model in R

12) Creating Product Bundles

Often when we visit a McDonald’s outlet, we intend to buy only a burger, but when we look at the meal menu, we end up buying the full mean instead of a single burger. This method of combining a few products and selling them as a single unit is called product bundling. It helps in increasing the sales of a business.

Creating Product Bundles

Project Idea: In this project, you will identify product bundles from the given sales data. While market basket analysis is commonly used for solving such problems, you will be using the time series clustering method. The two techniques will be compared to understand the significance of both methods.

Source Code: Identify Product Bundles from Sales Data

Recommended Reading: 50 Business Analyst Interview Questions and Answers

Professional Business Analysts planning to aim for senior roles will find business analyst projects samples in this section. A senior business analyst is often expected to possess knowledge of Big Data tools. Thus, you will find the projects described below rely on these tools.

13) Analyzing Log Files

If you are new to Big data projects and want to learn the basics of data analysis using Hive, then this project will be a good start. This simple project has been added to this section to prepare you for the next two projects.

Project Idea: This project is simply about analyzing log files of different users of a website. You will learn how to use Apache Hive to extract meaningful data insights by executing real-time queries.

Source Code: Hive Sample Projects-Learn data analysis using sample data for Hive

Most Watched Projects

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View all Most Watched Projects

14) Retain Analytics

Retail Analytics refers to the complete analysis of various aspects of a business, including customer behavior and demands, supply chain analysis, sales, marketing, and inventory management. Such deeper analysis assists in deeply understanding the business model and smoothens various decision-making processes.

Retain Analytics

Project Idea: In this project, you will work with the Walmart stores dataset and use various Big Data techniques and tools to perform retail analytics. You will explore how to use tools like AWS EC2, Docker-composer, HDFS, Apache Hive, and MySQL for implementing the full solution.

Source Code: Retail Analytics Project Example using Sqoop, HDFS, and Hive

Build an Awesome Job Winning Project Portfolio with Solved End-to-End Big Data Projects

15) Analyzing Airline Data

Data has become a huge asset for many industries, and the airline industry is no exception. They rely on big data to answer a few of the most vital questions like when the customers are likely to witness minimum delay in flight timings? Are older planes more prone to delays? etc. Project Idea: For this project, you will work on the dataset of an airline and find answers to questions like the ones mentioned above. You will be guided on how to ingest data and extract it using Cloudera VMware. After that, you will learn about preprocessing the data using Apache Pig. Next, you will use Hive for making tables and performing Exploratory Data Analysis. You will also get to explore the application of HCatloader and parquet through this project. Source Code: Hadoop Hive Project on Airline Dataset Analysis

Hey, Hey! The blog hasn’t ended yet. Going by what Steve Jobs said. “ ‘Learn continually. There's always “one more thing” to learn.’, we don’t want your learning journey to stop here. Check out more such Data Science Projects and Big Data projects from our repository to work on more exciting projects like the ones discussed in this blog.

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Top Business Analytics Projects to Sharpen Your Skills and Build Your Business Analytics Portfolio

Business analytics is the tool used by professionals to make sound business decisions. It fosters the profitability of a business and helps increase a business’s market value. This is why business owners are keen on employing business analysts or business intelligence analysts to help achieve their objectives. 

With the increase in demand for such professionals, you will need to develop cutting-edge skills to land a position. If you don’t want to get certified yet, you should consider completing business analytics projects. These projects will help you gain hands-on experience and showcase to employers your expertise and skill level in business analytics .

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5 Skills That Business Analytics Projects Can Help You Practice

Completing business analytics projects can set you apart from other job applicants. These projects will help you develop real-world experience. Whether your focus is on customer relationship management, financial management, human resources, marketing, or supply chain management, these projects will be invaluable to your growth. 

Best Business Analytics Project Ideas for Beginners 

Being a beginner in the field of business analytics does not mean you cannot pursue projects to boost your portfolio. There are plenty of beginner-friendly business analytics project ideas to help you grow your skills in business analytics. Below we curated a list of the best beginner project ideas to jumpstart your career.

Data on Employee Performance and Resignation

In this project, you will provide a company with data that can explain why employees are resigning. The goal is to take these results and use them to improve the business environment. You can take into account the employee’s distance from home, work culture, or job role. You should evaluate each factor with the relationship to resignation. 

Forecasting Sales of a Mall During December

A mall features a variety of shops and stalls that see high traffic during the holiday season. In this project, you should be able to determine which is the most popular product and how to ensure the shop does not run out of stock. You should check the current inventory and the customer segmentation to ensure you can forecast the sales properly. 

Predicting the Success of a Product

In this project, you can rely on your analytical skills to determine if a particular product will sell well in a specified market. For instance, you can focus on the entertainment industry. With thousands of hours of content being disseminated daily, it is quite challenging to establish which song or movie will do well. You will need to make use of historical data and models to make predictions. 

Predicting Sales for an Upcoming Car Design

This project involves taking a deep dive into customer needs and wants. You can work on a project to determine if a new car design, color, or shape will appeal to the target audience. There is a wide variety of cars available in the market to help you determine the most popular vehicle. 

Customer Segmentation

In this project, you will deal with a wide customer base of an organization. The main aim of the project is to provide the best customer segmentation to the business leader, development, and marketing team to design campaigns. You should check on the spending ability of the customers and the most popular products. 

Best Intermediate Business Analytics Project Ideas 

If you have confidence in your business analytics skills and would like to take on new challenges, you should pursue intermediate business analytics projects. These mid-level projects will open you up to new horizons in business analytics. They can also help in landing a well-paying job position in tech or other fields. 

Project Management and Business Analysis

You can get plenty of ideas by reading this paper on project management and business analytics. The paper covers lessons from A Guide to the Project Management Body of Knowledge and A Guide to the Business Analysis Body of Knowledge . The latter provides a comprehensive guide in the elicitation process, also referred to as enterprise analysis. 

The above-mentioned books are instrumental to improving your project management skills and informing you on best practices in the industry. You will start with identifying the organizational problem and finish by defining systems capabilities. 

Human Resources

This project involves automating processes, multidimensional analysis, self-service access, and recruitment methods. Your goal is to find ways to improve recruitment and retainment for a company while remaining within a set budget. This project will help you develop analytical skills in establishing the sensitive areas of a business that can lead to potential losses.

Business Analytics Capstone

If you have a computer science or business degree, you should consider working on this capstone project. This project-based course will help you learn real-world applications for data-driven decision making. By working on this project, you will familiarize yourself with using data to optimize businesses, maximize value, and make operations efficient. 

This capstone project will take business professionals through challenges faced by global companies such as Yahoo and Google. You will learn how to use data for addressing business challenges. It’s a curated project by Yahoo to help you master how to make data-driven decisions after complete evaluation. 

Sales Conversion Optimization

This is a great project to work on Return on Investment. Through this project, you will be able to develop campaign strategies that will positively impact business operations. You will also optimize the budget to be more impactful by utilizing methods such as email blasting and social media marketing.

Optical Character Recognition

You can choose to work on optical character recognition, which deals with converting text in images to typed text. You can find open-source project templates for creating optical character recognition software with Python and Swift. You can program an application that turns handwritten documents into typed ones. 

Advanced Business Analytics Project Ideas

These advanced business analytics project ideas can take your expertise to a professional level. These projects feature advanced concepts such as pattern matching, forecasting, sentiment analysis, graph analysis, and neural networks. Find out more about the business analytics project details and the skills you will gain below.

Credit Risk Classification Analysis

In this project, you can choose to focus on a particular financial organization or simply generalize. However, the more specific, the easier it will be to analyze the credit risk. You will start by analyzing the historical data of the customer, financial information, and loan purpose. 

You should check on factors like age, gender, marital status, job type, and income in your project. This classification tool should inform the business on the best cause of action when issuing credit or loans. 

Sales Data Exploration and Reduction

This project will help inform business leaders on the best course of action when it comes to remaining profitable. You can take a deep dive into the project to make it advanced by including the products or services that will generate more value or a higher ROI. You can also add customer segmentation to the project to help the leaders identify the target audience. 

Music Sales in America

This project involves assessing factors in music sales like genre, popular artists, and sales distribution. The project will require you to work with Tableau for data visualization. By the end of the project, you will be familiar with top musicians, data mining, data visualizations, and machine learning concepts. 

University Fundraising

To complete this project, you will need to include the degree that attracts the most funds, gift donors, and pledge deals. It is best to present this data individually in Excel or a similar tool. Your project should display your ability to conduct in-depth research, data analysis, data visualization, and statistical programming. 

Exploring Aircraft Hardware Suppliers

This is an excellent advanced project idea in business analytics that tackles the demand and supply of aircraft hardware. In the project, you will be expected to create a menu, explore orders, minimum purchases, forms of payment, and customer preferences. To make it more complex, you can also feature the shopping time. 

Business Analytics Starter Project Templates

To complete the named business analytics projects, you do not need to start from scratch. There are exceptional template samples that can help you work on your projects seamlessly. Find a list of business analytics starter project samples below. 

Next Steps: Start Organizing Your Business Analytics Portfolio

A lady holding papers with graph drawings. To succeed in business, you cannot underestimate the power of big data, business analytics, and business intelligence.

A well-curated portfolio might be what you need to get to the next level in your career. After you have amassed solid real-world skills from the business analytics projects, you need to know how to present them for job applications. The tips we list below will guide you to designing a winning resume.

Pinpoint Your Achievements 

Use your portfolio for marketing your skills and experience. Always try to capture the recruiter’s attention from the onset by displaying your best work. Often hiring managers receive hundreds of applications, so it’s important for you to highlight your achievements to showcase your skills. 

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"Career Karma entered my life when I needed it most and quickly helped me match with a bootcamp. Two months after graduating, I found my dream job that aligned with my values and goals in life!"

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Key in Relevant Information 

Align your portfolio to the job requirements and description. Use these job sections to guide you in adding relevant information to your portfolio. You will gauge the skills and experience needed, which will help you curate the best-suited portfolio. 

Make It Simple 

You must present a straightforward portfolio. Your portfolio should have concise documents which are organized. Keep it updated so that it can be easier for the employer to track your progress over the years. 

Business Analytics Projects FAQ

Yes, a well-curated business analytics portfolio can lead to a well-paying career. As a professional, consider aligning your documents according to the job requirements. This will significantly increase your chances of employment. 

No, you do not need to learn how to code to complete a business analytics project. However, having basic knowledge of software programming can be highly beneficial. You will have a broad understanding of the technical side of the business.

There are four different types of business analytics. There are descriptive, diagnostic, prescriptive, and predictive.

No, business analytics projects are not difficult to complete. As long as you have the motivation and experience to complete a project, you will be able to see it through. Ensure you have a strict schedule to help you remain consistent. 

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capstone project in business analytics

capstone project in business analytics

The Best 150 Capstone Project Topic Ideas

10 May 2022

Quick Navigation

❔What is a Capstone Project?

Capstone Project Ideas:

✅Capstone Writing: 10 Steps

The long path of research works ahead, and you can’t find any capstone project ideas that would be interesting and innovative? The task can seem even more challenging for you to feel all the responsibility of this first step. The top 150 capstone ideas presented below aim to make a choice not so effort-consuming.

With the list of the capstone project topics we've picked for you, you'll be covered in major subjects. Continue reading, and you'll get ideas for capstone projects in information technology, nursing, psychology, marketing, management, and more.

What is a Capstone Project?

Educational institutions use the capstone project to evaluate your understanding of the course on various parameters. For the students, the work on the project gives an excellent opportunity to demonstrate their presentation, problem-solving and soft skills. Capstone projects are normally used in the curriculum of colleges and schools. Also called a senior exhibition or a culminating project, these assignments are given to finish the academic course.

This assignment has several different objectives, among which are the following:

It's not that easy to pick the right capstone paper topic. The problem intensifies as each student or separate teams have to work on a single assignment which has to be unique. The best capstone project ideas may possibly run out. However, whatever topic you opt for, you’d better start your preparation and research on the subject as early as possible.

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Amazing Capstone Project Ideas for Nursing Course

Studying nursing is challenging, as it requires a prominent theoretical foundation and is fully practical at the same time. You should have to do thorough research and provide evidence for your ideas, but what to start with? The preparation for your capstone project in nursing won’t be so overwhelming if you make use of these capstone title ideas:

Attractive Computer Science Capstone Project Ideas

Computer science is so rapidly developing that you might easily get lost in the new trends in the sphere. Gaming and internet security, machine learning and computer forensics, artificial intelligence, and database development – you first have to settle down on something. Check the topics for the capstone project examples below to pick one. Decide how deeply you will research the topic and define how wide or narrow the sphere of your investigation will be.

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Several High School Education Capstone Project Ideas for Inspiration

High school education is a transit point in professional education and the most valuable period for personal soft skills development. No wonder that the list of capstone project ideas in high school education involves rather various topics. They may range from local startup analysis and engineer’s career path to bullying problems. It’s up to you to use the chosen statement as the ready capstone project title or just an idea for future development.

Capstone Project Topics in Information Technology – Search for Your Best

Information technology is a separate area developed on the basis of computer science, and it might be challenging to capture the differences between them. If you hesitate about what to start with – use the following topics for capstone project as the starting point for your capstone research topics.

Psychology Capstone Project Ideas

Society shows increasing attention to mental health. The range of issues that influence human psychology is vast, and the choice may be difficult. You’ll find simple capstone project ideas to settle on in the following list.

Stuck with finding the right title?

Get plenty of fresh and catchy topic ideas and pick the perfect one with PapersOwl Title Generator.

Capstone Project Ideas for Management Course

Studying management means dealing with the most varied spheres of life, problem-solving in different business areas, and evaluating risks. The challenge starts when you select the appropriate topic for your capstone project. Let the following list help you come up with your ideas.

Capstone Project Ideas for Your Marketing Course

Marketing aims to make the business attractive to the customer and client-oriented. The variety of easy capstone project ideas below gives you the start for your research work.

Best Capstone Engineering Project Ideas

It’s difficult to find a more varied discipline than engineering. If you study it – you already know your specialization and occupational interest, but the list of ideas below can be helpful.

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Editors on PapersOwl can edit your paper and give recommendations on how to improve your writing:

Capstone Project Ideas for MBA

Here you might read some senior capstone project ideas to help you with your MBA assignment.

Capstone Project Ideas for an Accounting Course

Try these ideas for your Capstone Project in Accounting – and get the best result possible.

Capstone Writing: 10 Essential Steps

Be it a senior capstone project of a high school pupil or the one for college, you follow these ten steps. This will ensure you’ll create a powerful capstone paper in the outcome and get the best grade:

Preparation of a powerful capstone project involves both selection of an exciting topic and its in-depth examination. If you are interested in the topic, you'll be able to demonstrate to your professor a deep insight into the subject. The lists of ideas above will inspire you and prepare you for the successful completion of your project. Don’t hesitate to try them now!

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capstone project in business analytics

Capstone Projects – Great Lakes Business Analytics Program


I have been associated with the Great Lakes Business Analytics Program as a visiting faculty for some time now. This is one of the ways, I interact with people wanting to make their career in analytics. The energy and the desire to make a career in business analytics in some of these students is just contagious!

As part of the curriculum, people undergoing this course are expected to complete a Capstone Project. This Capstone Project is like a climax at the end of a yearlong movie – it looks difficult at the start, but everything you do in the entire movie comes together at the end.

I had the privilege of sitting in the evaluation panel for a few projects. In today’s article, I plan to give an overview of what happened in these projects.

Why share these projects?

Well, there are a few reasons, why I wanted to share these projects in form of an article with a larger audience:

I have already informed Great Lakes about the article and I’ve published this with their consent.

Overview – How do these projects work?

As mentioned before, every person undergoing this course is expected to submit a Capstone Project. In order to do this project, a project group is formed with participants from diverse backgrounds. These groups, then work along with a mentor to complete these projects over a period of 4– 5 months. About 80% of these projects happen with mentors from industry. Mentors from various companies like Value Labs, Whiskkers Marketing Pvt. Ltd., BRIDGE i2i, Analytics Vidhya participate in helping students with these projects.

Importance of Capstone Project for students

Analytics is a very hands on subject. I personally believe that until and unless you complete a few projects end to end (i.e. from data collection to building a model to implementing a model), your knowledge and approach stays theoretical in nature.

The same view was reflected by students, when I talked to a few of them. Here is one of the student sharing his experience undergoing the capstone project:

During our course at Great Lakes, we learnt about various techniques like, ways of cleaning-up data, multiple algorithms for analysis and modeling, goodness of fit to check model fitness and had numerous sessions on business intelligence. But it is the Capstone Project that introduced us to the real world challenges of applying our learning, testing adequacy, usefulness and subjectivity of certain algorithms. We also got some real time insight into the processes and steps involved in a typical analytics project. Without Capstone Project our learning would have remained incomplete.  –  Sriram Alagarsamy, Great Lakes PGPBA Alumnus

The Projects

In the rest of this article, I’ll provide a few examples of the Capstone Projects, which happened in last batches of Great Lakes and the industry sponsors / mentors were happy to share the project details through this article.

Project 1: Credit Default Prediction

Students: Kanthimathi Gayatri Sukumar, S.R.Balaji, S.Ramnath, Rudragouda Patil, Mithur Niranjan

In this project, the students had built several models to predict credit default for 2 wheeler loans in villages in India. The variables available to the candidates included:

The group had built several models including Logistic regression, Classification tree – CART, Classification tree (Ensemble) – Random forest, Neural networks and Discriminant analysis. Here is the comparison of various modeling techniques:


The group finally used Logistic regression because of high accuracy and ease of insight generation (rather than a black box approach to modeling)

Project 2: Statistical Analysis of Consumer Durables Retail Sales

Students: Soumya Tiwari, Remina Surendrababu, Arnab Majumdar, Vijayalekshmi L, Siju Joseph

The project team analyzed about 0.5 million transactions for a retail chain having 20 branches across Chennai. The team collected the data for a period of three years to find a reasonable practical solution to the following business problems faced by a consumer durable retail chain:

This group used R and built a recommender system using Apriori algorithm.

Project 3: Web & Text Mining – Sentiment Analysis

Student: Anjana Agrawal

Anjana has been doing freelance IT consulting to clients across the globe. Her Capstone Project required her to enable a political organization to understand people’s concerns, views and sentiments on topics in near real time. She also has a publication, which came out of her work (commendable! I must say).

The project started by obtaining input text data from “Twitter” for one of the leading political organization and the tweets were scored for sentiment analysis. Output generated in terms of “Common Key Words”, “Association between common key words”, “Sentiment Score” was observed and analyzed for a period of approx. 3 weeks. This output was important for the organization considering the fact that this political organization was campaigning for the elections scheduled in near future and based on the “Citizen” sentiments, organization was able to refine their next course of action.


The project ended up being used by the party in real time and helped them in addressing the concerns of its people quickly.

Project 4: Credit card – Risk Analytics

Students: Amit Madan, Praveen Panwar

The objective of this project was to develop a model to calculate the probability of default (PD Model) for credit card holders of a bank. The model was supposed to be run after the customer has spent more than a year with the bank and predicts the probability of default over a period of next 3 months.

Amit & Praveen had more than 2 million data points with 20 variables (18 numeric and 2 character) to start with. They created more than 50 additional variables based on their internal brainstorming. After removing variables with high correlation and the insignificant variables, they used Logistic Regression to build the model.

The final model had a concordant ratio of 91.4% and a list of 230%. Here is the Lorenz curve for the same.


It was amazing to see the amount or learning the students had undergone through this project. Even if you join a bank as an analyst, it would take you a few years before you can get your hands dirty on a problem like this!

Amit reflected similar sentiment in my discussion with him later:

There are three important steps in the computational modelling of any physical process (1) Problem definition (2) mathematical model and (3) computer simulation. CAPSTONE provided for an opportunity to synthesize domain expertise, mathematical representation and computational skills to re-produce a modelling framework so as to be able to cull out the insights present in a data. It was by virtue of CAPSTONE, we could apply all of what we had learned at Great Lakes and it helped generate an urge to keep undertaking similar assignments for sustained mental stimulation.   –  Amit Madan, Great Lakes PGPBA, Alumnus

Project 5: Developing Least Cost Effective Intervention in Schools

Students : Balamuril S, RamKumar R, Senthil J, Sreeraman K, Sriram A

This group applied the power of analytics to impact government aided schools in 5 districts. They created clusters of schools, developed insights about their performance and translated them into quality improvement program for these schools.

They further created a model to rank these schools, simulate the effect of government interventions and then measure them as well. The project should not only impact the 5 districts, but can have a far larger impact by implementing these insights for schools across the nation.

Project 6: Lead Generation for Health Insurance Firms using Web and Social Media Data

Students : Harpreet Kaur, Aneet Sachdeva, Peeyush Tiwari

This group first collected open data and social media data, applied text mining and natural language processing (NLP) techniques to extract features out of this data. They then applied various clustering and bag of words techniques to pull out insights into insurance purchase behavior. Some of these groups were identified as high potential leads for Health Insurance products.

As you can see, the projects varied from predicting default in rural regions to helping parties contest elections. It was heartening to see the output from this group of people, most of whom had very little knowledge about analytics a year ago.

I hope this article would provide learners in analytics with a few ideas to do their own Capstone Projects and would have provided a glimpse of the program to those interested. You can read more details about the program here.

If you like what you just read & want to continue your analytics learning,  subscribe to our emails ,  follow us on twitter  or like our  facebook page .

capstone project in business analytics

About the Author

Kunal Jain

Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.

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capstone project in business analytics

In this section

Business Analytics Capstone Experience

The Business Analytics Capstone Experience allows students to work on real-world business problems using data and statistics.

Graduate students work with a UM-Dearborn faculty advisor and a mentor from a sponsoring company to model, analyze and recommend a solution for a significant business problem.

Sponsoring a Capstone Project

The curriculum for the Master of Science-Business Analytics  in the College of Business prepares students to deal with the challenging task of deriving deep insights from the vast array of structured and unstructured data in a variety of business areas. The program prepares students to pursue careers such as a data scientist or analyst.

Capstone Project Overview

The capstone project is the core of the MS-Business Analytics curriculum. This 15-week course emphasizes a team-based learning experience in which students conduct real-world analytics projects using data provided by the sponsoring organization. Since Winter 2016, students have completed 25 projects with 9 sponsoring organizations. Some of the industry sectors represented by our sponsors include manufacturing, healthcare, energy, retail, logistics, information technology, and service. Student projects have included optimal supply-chain logistics configuration, health-care services profitability analysis, predictive modeling for parts classification, analysis of customer satisfaction in a call center, forecasting weather-related power outages, data-modeling for smart mobility, augmented analytics & conversational analytics for data mining applications, information assurance trend analysis, and learning analytics.

Why Sponsor a Capstone Project

Sponsoring a project provides MS-Business Analytics students an opportunity to gain experience applying their coursework to real-world business problems.

It also offers the sponsoring organizations the opportunity to work with our students.  Many organizations make formal offers of employment to project participants after their work in the capstone project.

Only select students participate in the Capstone course.  These students are selected on the basis of:

Course Deliverables:

There is no cost to sponsor a project.

Requirements for Sponsor

Project teams sign a non-disclosure agreement to protect the privacy of the data and other information shared by the sponsor. Sponsors may anonymize business-sensitive information and other technical details.

Project Details

At the start of the semester, the sponsor and students meet to discuss the following: 

The goal of the project is for students to:

During the project, student teams maintain regular communication with the project sponsors through scheduled site visits, web meetings and weekly progress updates. The Faculty Coordinator tracks project progress with technical reviews and updates with the student teams throughout the semester.  In addition, the Faculty Coordinator and project sponsors jointly conduct mid-term progress reviews and provide feedback to the student teams.

The University provides student teams with access to an extensive portal of prominent software in a cloud-based environment, which students will use on their projects.

At the conclusion of the project, the student teams will make a public presentation of their findings to the sponsor, College of Business faculty, staff and students.

View the capstone project syllabus .

Project Schedule

The Capstone project course is offered two times a year, during Fall and Winter semesters. We welcome your inquiries about sponsoring a Capstone project. We are always planning for projects for upcoming semesters. The tentative schedule is as follows:

Capstone Projects for Winter 2022

Evaluating the use of my learning analytics (myla) within canvas at the university of michigan.

My Learning Analytics (MyLA) is an optional additional dashboard design tool embedded within Canvas. It offers assignment planning, grade calculations, and resources accessed features to help students engage in self-regulated learning. We analyzed student, course, and log data for 3,929 students enrolled in 61 courses offering the MyLA tool over 4 terms. Using this data, patterns of student activity were identified with the tool and tested for correlation between the use of the tool and course performance.

Multiple methods were developed to classify and separate students into two groups: users of the tool and non-users. The data was used to identify any similar academic or demographic characteristics among students. After analyzing the data, it was determined that there is a significant positive difference between users and non-users of the MyLA program when it comes to course performance. This difference in final course grade increases in magnitude and significance when users are determined by having two or more distinct weeks active in MyLA.

University of Michigan Information and Technology Services - Vulnerability Trend Analyses

This project identified and analyzed all the departments across the University of Michigan-Ann Arbor that are vulnerable to hacking.

The student team used Tenable.io , an industry-standard tool used to identify hacking risks within an organization's IT systems. The tool provided a massive data set containing all UM IP addresses, each of which was rated as far as its vulnerability to a cyber attack. Students matched this list with a file containing department names and their corresponding subnets.

Students performed data wrangling and data filtering on these two files to retain IP addresses corresponding to severe CVSS (common vulnerability severity rating) and VPR (vulnerability priority rating) ratings. Students then used the Python tool ipaddress to map IP addresses and IP subnets from either of the files to produce a list of the departments that are most vulnerable to hacking. After the mapping process, students analyzed and created a data visualization of the list of IP subnets and departments to identify how often each department was flagged a vulnerable to hacking. The students repeated this analysis over three consecutive months.

The students' work identified the UM departments which are the most vulnerable to hacking -- which turned out to be UM's Information Technology Services itself, followed by the College of Engineering.

Recent Projects

University of michigan project: conversational analytics using google dialog flow.

With the rise of messaging apps and social media technology being used as a main form of communication, U-M's Office of Budget and Planning wants to be able to quickly and conveniently analyze student survey data over the last 5 years. Gathering useful information about student needs and expectations is vital to help the University decide which technologies they should adopt to communicate with students to maintain a better student-university relationship. Chatbot and Voice Assistant are primarily being used to support staff by gathering the information they need from the student survey data. This project will task students to utilize Google assistant to answer questions and Dialog-flow to create a seamless interaction between users and system.

University of Michigan Project: Augmented Analytics and Visualization of Student Services Activities

U-M’s Information Technology Services has collected a lot of data over the years through various activities across the Ann Arbor campus. The Office of Budget and Planning wants its staff to have the ability to run reports and gain insights from the UMay survey data. Students will be tasked to design a model by implementing and creating Augmented Analytics that will connect the end-user to this large set of raw data. This will include the ability to process verbal queries and respond with visual analytics, which will make it easier for the end-user to understand the results.

Ford Motor Co.

Process for generating an origin-destination demand matrix for use in a commuter ride-sharing simulation at ford smart mobility.

Ford Motor Company has expanded into mobility services with the purchase of a startup company, Chariot, which offers a carpooling service to commuters in select urban areas and uniquely allows potential customers to vote on new commuter routes. To support Ford and Chariot in identifying new commuter routes in cities where the company is not operating, this research effort created a process that simulates commuter origin and destinations, the number of commuters, and time of departure. The process selected San Francisco, CA as a starting point in part for verification purposes because Chariot already has operations in the city. Results indicate the process properly simulated commuter flow. Specifically, commuter’s origin locations were highly dispersed across San Francisco, but the destination locations indicate commuters are traveling towards areas of high employment. The process also accurately simulated departure times associated with the rush hour commute. In summary, the process created can be replicated to model commuter traffic patterns in other cities and identify where large of commuters are traveling from and to and during what time of day. Thus, the process provides Ford and Chariot commuter data to help guide early business decisions. An end-to-end analytics framework was utilized to process publicly available data from a very large number of sources by utilizing advanced data mining, visual analytics and simulation techniques to generate traffic flow inputs for advanced transportation network and simulation models.

Modeling for Predicting Power Outages due to Weather Events for DTE Energy

DTE Energy, the electrical service provider for Southeast Michigan, allocates a great deal of resources toward managing outages, particularly those caused by big weather events. This research project aimed to develop a series of models which are geographically sensitive (at the service center level) to predict number of power outages per day based on weather data. Using an ensemble of neural networks, a model for each service center was created that is sensitive to three different scenarios. These models, specifically those belonging to the four service centers which experience the greatest number of electrical service interruptions, predict number of outages in that service center to an industry benchmark level of accuracy. Further, one scenario—high temperature and high wind speed days—predicts outages substantially beyond industry benchmarks. Finally, we discuss our attempt at a more time sensitive model, predicting outages hourly. An end-to-end data analytics framework was utilized to process large disparate datasets by utilizing advanced data mining techniques to cleanse, merge and prepare data for modeling utilizing predictive modeling, and classification & forecasting algorithms. This work has enabled DTE Energy to better plan their labor and other resources in restoring power in a more efficient manner.

Stefanini IT Solutions Inc.

An analytics approach to managing inbound call support at stefanini it solutions.

Harnessing the power of data and analytics is the first step in driving operational efficiencies for the business of the future. Stefanini is looking to gain data driven insights into two of their existing call-center processes – inbound call handling process and the existing service ticket creation process. Stefanini currently maintains and captures data related to these two processes separately. The purpose of this project is to combine the call related data with the corresponding tickets and assist Stefanini to gain a better understanding of on what impact the issue types have on the duration of the calls. The analysis will also help Stefanini identify key areas to drive automation, deploy additional employee trainings and optimize the existing staffing models that can eventually generate operational efficiencies for the company. An end-to-end analytics framework was designed by effectively combining the two disparate data sets by utilizing exploratory data analytics, visualization and advanced analytics techniques to generate key insights to help drive efficiencies and automation for Stefanini.

capstone project in business analytics

“Students had a short period of time to work on large scale issues, but they were able to find opportunities within the data set, and indeed, Ford will be implementing solutions in this space.” - Alan Jacobson, Ford Motor Company

Students with project sponsors

“The work developed by the students is a useful addition to our vulnerability reporting capability.”

Students with project sponsors

“Overall, the students did very well. They presented some research findings that began to address some of the important questions about the relationship between MyLA use and academic performance.”

College of Business Graduate Office

employees working with data on laptop and tablet

Putting It All Together: Your Analytics Capstone Project

Given the emphasis our Online MSBA program places on developing a well-rounded, multifaceted skill set, it is no surprise that the program concludes with a culminating collaborative analytics project. In the Business Analytics Capstone Project course, students are asked to apply everything they have learned in the program toward solving a challenging real-life business problem.

Each graduating cohort in the Online MSBA program will have a distinct capstone project experience featuring unique data sets provided by W&M’s impressive roster of corporate partners. This is no ordinary business school assignment: It’s your opportunity to deploy your new analytics, data visualization and communication skills on real data, with a real-world impact on a major organization’s strategic decisions and demonstrate excellence across each of the Online MSBA program’s four pillars .

Connect Beyond the Capstone With W&M

Show off your skills.

In completing the capstone course, you’ll have the opportunity to:

Capstone Snapshot: Data Feast

two hands working on AI Data Platform

The capstone experience for the Online MSBA cohort graduating in spring 2020 was the Data Feast competition , which pitted two teams of Online MSBA students against two teams of students from the on-campus MSBA program to analyze a data set and offer strategic insights to guide the expansion efforts of an up-and-coming sports and entertainment company. Two winners were declared in each of the areas of technical skills and business acumen, and the winners of the technical challenge was one of the two Online MSBA teams!

Read more about how this experience helped 2020 MSBA graduates Jamar Jenkins and Cheryl Ngo synthesize their new skills and solidify their confidence.

Data Feast 2020

The capstone helped me realize that there is a lot of work to be done for analytics problems aside from just the exciting new coding you've learned. There's cleaning to be done, there are questions to be asked, there's a background to be understood and there are end goals by the business involved. There are a lot of different layers to things beyond just ‘Here's an answer to a simple question.’

Interested in Our Online Programs?

Priority application deadline, application deadline.

Two professionally dressed students giving a presentation at the Playa Vista Campus

Gain Real-World Experience

The M.S. in Business Analytics capstone project is designed to develop your problem-framing, teamwork, project management and communication skills while integrating all of your previously gained technical knowledge by managing a business analytics project using real datasets provided by clients and other relevant databases.

Built around student teams, the capstone project gives students the opportunity to provide business analytics solutions to real organizations under the guidance of on-site corporate managers and faculty members. Potential capstone projects cover a wide range of industries in the Los Angeles area, with a focus on engaging the surrounding Silicon Beach community.

The LMU M.S. in Business Analytics Advisory Board is highly involved with our program's capstone projects, providing guidance and support in the development of the curriculum, as well as directly to the student teams throughout their project.

Past capstone projects include:

By giving you the opportunity to manage a business analytics project from conception to final presentation of findings, you gain valuable work experience that will provide numerous benefits as you look toward your future career path .

Headshot of Joshua Rotuna

Past Capstone Project Clients

Collage of institution's logos including Adobe, Qdoba, RPA, Fandango, Future Data Lab, Hawthorne Advertising, Los Angeles County Economic Development Corporation, RMDS and Children's Hospital Los Angeles.

Interested in Partnering With Us?

If your company is interested in becoming a client for a team of M.S. in Business Analytics students, please email us with contact information and the scope of the proposed project, and a member of our faculty will be in touch.

Luke Parson

Google Data Analytics Capstone Project

Bellabeat case study report.

Luke Parson — 2/20/2023

Link to Executive Presentation


Below is a detailed report on the analysis of current trends in the wearable fitness tracker industry, followed by recommendations on how Bellabeat can use these trends to improve their marketing strategy.

Bellabeat is a growing company that specializes in health-focused smart products for women. One of the main goals of the company’s leaders, Urška Sršen and Sando Mur, is to continue to unlock new growth opportunities and become a major player in the global smart device market.

Business Task:

The executive team wants to know how consumers use non-Bellabeat smart devices in order to draw insights for the marketing strategy of the company’s own smart device products. In this specific case, the Bellabeat Leaf.

Data Description:

The dataset used for this analysis was device tracker data from thirty Fitbit users, including detail on physical activity, heart rate, sleep, and weight. Data was generated through responses to a survey distributed through Amazon Mechanical Turk from March 12, 2016 to May 12, 2016. This is a public dataset made available on Kaggle by user Mobius. For this particular analysis, data on activity level and sleep were utilized.


The actual data only includes tracker output from April 12, 2016 — May 12, 2016, making the observable timeframe relatively small. The survey is now almost seven years old, meaning the data is not current and could be subject to changes in wearable device trends and usage.

The data actually contains thirty three unique users (not thirty) who submitted physical activity, twenty four submitting sleep data, and eight who recorded their weight. The sample size of thirty three and twenty four is small for physical activity and sleep respectively. Weight data was not considered in this analysis as the number of observations was deemed too small.

Lastly, the lack of demographic information (gender, age, location, occupation, etc.) limits the context of this data but would be useful for future analysis.

Data Preparation:

Eighteen files were included in the dataset. Each physical activity category was contained in separate files along with one file combining all physical activity details. Data was also available on a daily, hourly, and minute timeframe. For this analysis, I was focused only on daily activity and sleep. Therefore, I selected the following three files to use for my analysis — “dailyActivity_merged.csv”, “hourlyIntensities_merged.csv”, and “sleepDay_merged.csv”.

Since the data was relatively small, I used Excel as my data manipulation tool. Overall, I completed six steps to clean and transform the data.

I relied on a series of questions to help drive my analysis. Below are the questions and associated code that helped me uncover the answers and subsequent insights from the data.

1. What days were users the most active?

2. How many days during the survey time frame did users wear their fitness device?

3. What were the total times of each type of activity recorded?

4. What time of day were users the most active?

5. How many hours of sleep were users getting a night? Was this enough sleep according to medical recommendations?

6. What was the relationship between hours slept and sedentary activity?

7. How many hours a day did users wear their devices?

Data Visualization:

I used a combination of Tableau and RStudio to produce the visualization for my final presentation. Tableau was relied on for simpler bar charts and heatmaps, while RStudio was utilized for more detailed scatter plots and histograms to uncover trends and relationships.

Additional views created in Tableau can be found here .

Based on the analysis performed on the available data, I arrived at a few conclusions regarding how device owners utilized their wearable fitness trackers.

It seems like the majority of users are casual wearers of the device, as sedentary activity is the highest tracked category on a per minute basis. Because of this, athletes and individuals who only wear the device to track specific workouts or sports would probably fall outside of the target market and require a more specific product.

Activity levels during the week were mostly constant and only saw slight deviations on weekends. Activity levels also occurred within distinct buckets of time, mostly the middle of the day and early evening. These timeframes point to users who likely follow a set daytime routine. It would be reasonable to conclude that these users are working professionals and follow a corporate lifestyle (i.e. a “9 to 5” job).

Varying hours of sleep each night indicate that users do not have a consistent sleep schedule. There was a mostly linear relationship between time in bed and hours slept, suggesting that varying hours slept are likely due to inconsistent times going to bed or waking up, not from trouble falling asleep while in bed.


Below are the specific recommendations for Bellabeat to improve its marketing plan.

By incorporating these strategies, Bellabeat will continue to build on it’s early success and capture a larger market share of the global smart device industry.

More from Luke Parson

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MS Analytics

MS Analytics

Capstone Project

The MS Analytics  p rogram  c apstone  is a career enhancer.  S tudents utilize real data from their organization  (or another)  and partner with a  project coach  to build a predictive model.  The individual project is completed over the  five semester s.   Graduates have earned significant raises  because of  the ir  capstone  projects .   The Cohort of 2021 reported an average  annual  estimated value of their capstone of $18.2 M.  

capstone project in business analytics

Examples of capstone projects submitted by students according to industry:




Real Estate

Social Impact Analytics


Food Manufacturing/Distribution


Human Resources



Capstone Project Frequently Asked Questions

1. Do I have to know what my capstone project will be when I apply?

We will begin discussing the capstone project in orientation, but you won’t have to submit an initial topic proposal until the end of the first semester.

2. Will my data be secure?

Your data never leaves you and is not stored on university servers. We recommend you anonymize, rescale, and sanitize your data. Your project coach can sign a non-disclosure agreement to further ensure confidentiality.

3. How large does my dataset have to be?

The answer really depends on your business problem/question. Our definition of big data is n=all. You will discuss data with your project coach to determine what variables are needed.

4. Will I be required to publish my project or present it?

Students typically do not publish their findings due to company confidentiality agreements. Peer presentations are made, but specific variables and findings do not have to be shared as we are interested in the process of modeling more than the specific outcomes.

5. Is the capstone project individual or group?

Our capstone project is an individual project specific to each student and his/her organization or interests. It is a unique feature of our program which is both time and resource intensive, but yields enormous return on investment.

6. What makes a good capstone project?

Think about what keeps your boss up at night? What is her/his (or your) bonus based on? Typically a project that is interesting to your employer makes a great project.

Connect with the MS Analytics Program


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Master of Science in Business Analytics | Blended Learning & Capstone

Blended Learning & Capstone


Blended Learning


Solving Data Science Challenges to Optimize your Business.

The intersection of business savvy and technical expertise.

The MBAn Program at MIT Sloan has been ranked #1 in the world since its inception in 2016. But we don’t rest on our laurels. Our faculty, staff, and students are committed to continuously improving our knowledge and our impact. Each year, our students take on greater challenges and keep iterating.

Across industries and functions, our teams of 2 students and a faculty mentor are bringing cutting edge data smarts with an eye to solving practical business problems. And they keep knocking it out of the park.

As we step into the future, the need for high quality analytics isn’t slowing down. And neither are we.


What is the Analytics Capstone?

The rigor of the MIT Sloan Master of Business Analytics program prepares students for careers that apply and manage modern data science to solve critical business challenges. The Analytics Capstone Project is a core component of this program, giving students real-world experience solving data challenges from organizations around the world.

MIT Sloan welcomes proposals from organizations around the world and from every industry and sector to sponsor student groups for the 7-month project course. Dedicated teams of students use analytical tools to solve your key business challenges and present applicable solutions at the completion of the capstone period. The teams perform their work under confidentiality agreements and the results are the sole property of the respective sponsors.


Past Projects

We work across industry verticals and functional areas to solve big problems for businesses that are shaping how we use data to understand profitability, operations, risk, and cost-savings. We’ve worked with Fortune 500 companies, startups, and nonprofits to address their business challenges and we’re proud of what our students have accomplished. Take a look at some of our past projects, and we guarantee you’ll find one that speaks to you.


See our Projects in Action

Each year, our students present their final products at a Capstone Showcase. This event is a wonderful opportunity to ask questions, meet the sponsors, and hear more about what the Capstone process is like from the people who’ve just been there. We’d love to welcome you in August and introduce you to this incredible opportunity!


Ready to Solve your Problem?

capstone project in business analytics


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Excel will be used for the data cleaning process and for removing errors from data. R programming language will be used for analysis and visualization.

Note: SQL, Tableau can be used for data manipulation and data visualization here as well, but using R all functions were performed.

Bellabeat is a high-tech manufacturer of health-focused products. As a junior data analyst working with marketing analyst team at Bellabeat, I have been asked to focus on one of Bellabeat’s products and analyze smart device data to gain insight into how consumers are using their smart devices. I have performed analysis on data to give recommendations.

The data set is Fitbit Fitness Tracker Data taken from Kaggle which contains personal fitness trackers from thirty Fitbit users. It contains 18 CSV files

Business objectives

What are some trends in smart device usage?

How could these trends apply to Bellabeat customers?

How could these trends help influence Bellabeat’s marketing strategy?


• Urška Sršen: Bellabeat’s co-founder and Chief Creative Officer

• Sando Mur: Mathematician and Bellabeat’s cofounder; a key member of Bellabeat’s executive team

• Bellabeat’s marketing analytics team: A team of data analysts responsible for collecting, analyzing, and reporting data that helps guide Bellabeat’s marketing strategy.

FitBit Fitness Tracker Data (CC0: Public Domain, data set made available through Mobius)

#Data Credibility

There is no demographic data about users, hence women data cannot be extracted. Overall, data is 6 years old and would not be helpful in a fast moving technology market.


• We can see higher weight people(above 120kg) are more sedentary. so we should target specifically below 65kg but between 90 and 120kg people are very or fairly active - seems like high weight people are trying to lose weight and exercise more than normal people but they have less (very active distance) which means they run/jog less and are using indoor activities to stay active such as gym

• less than 70kg as they are active but won’t be willing to pay a lot because they are not passionate, they have more active distance though meaning they run/walk more. however, between 90 and 120kg people are passionate and would be willing to spend more money

• People are most active in the start of month and middle of month while data only collected for April and May.

• Step total decreases with weight, above 100kg steps decline. People who take more calories have more steps there is a linear relationship, while active people sleep less than 400 minutes and people between 80 and 100kg take most calories.

• Bellabeat’s marketing team can encourage users by educating and equipping them with knowledge about fitness benefits, suggest different types of exercises, calories intake and burn rate information on Bellabeat’s application.

• Most people use fitbit to track steps and calories burned, people don’t use to track sleep much. I will suggest focusing on steps, calories more than sleep in application

• The relation between steps taken vs calories burned and very active minutes vs calories burned shows positive correlation. So, this can be a good marketing strategy.

• If users want to lose weight, it’s probably a good idea to control daily calorie consumption. Bellabeat’s can suggest some ideas for low-calorie lunch and dinner.

• The Bellabeat app can recommend reducing sedentary time.


Guide to the Business School Capstone Project - Types & Examples

B-School Search

An MBA capstone project is the final step in many MBA programs. It’s here that MBA students put all that they’ve learned into practice by analyzing a meaningful and strategic business question. Often, this involves hands-on work within an existing company, but not always: MBA capstone projects can take the form of startup business plans and business simulations, too.

No matter their format or focus, each capstone project is likely to be the most intensive, and possibly the most rewarding, feature of an MBA candidate’s journey.

A capstone project is not the same as a thesis project, although they do share some qualities. Thesis projects are focused on theory and research, and based on the type of situations one would face in academia. Often taking the form of a large research paper, thesis projects can last the entire final year of an academic program, and some students may even begin before that, with the ultimate goal of contributing new knowledge to the canon of business research.

MBA capstone projects, by contrast, are more practical and similar to situations one would face in the business world. Here, students work in teams to answer strategic business questions. MBA capstones are hands-on immersions with real-world consequences, and they can have a major impact on an MBA graduate’s program experience, as well as their career.

To see some examples of MBA capstone projects, and to get a walkthrough of the general process, read on.

Stages of an MBA Capstone Project

Most MBA capstone projects take place during a program’s final year and can last anywhere from four weeks to a full semester. They often include some form of instruction (whether through prerequisite courses or scheduled advising) along with practical application.

While MBA capstone programs will vary in format from program to program, they generally include the following stages:

It’s not necessarily over after the final presentation, either: some capstone projects carry over beyond the MBA program, leading to successful startup businesses, offers of employment, or investment opportunities.

Choosing a Capstone Topic

Many MBA programs provide some structured options for choosing a capstone topic. This can mean students are allowed to select from a list of possible partnership opportunities; it can also mean that faculty advisors will work with students to find a topic that meets the student’s strengths, weaknesses, and goals. But in other programs, MBA students are given more freedom to choose both their topic and their partner organization.

In their capstone project, MBA students should select a topic where they can answer a meaningful and strategic business question: one that’s complex enough to warrant significant time and energy, but also realistic enough as to be achievable. These are not theoretical questions, though; each one is tailored to a specific real-world business.

Some examples of MBA capstone topics include:

It’s critical for the capstone topic to be specifically relevant to the partner company or organization. To this end, MBA students should heavily research the company’s strengths, weaknesses, and objectives before selecting their topic.

Similarly, MBA students should turn that lens on themselves, too: what problems do they want to explore in their business careers, what causes do they find interesting, and how can their own unique skill set be best put to use?

How an MBA Capstone is Graded

Some programs provide MBA candidates with a rubric for how their capstone will be graded, while others do not. Most capstones are graded through their ability to demonstrate key business skills (theoretical, practical, applied, and reflective) across functional areas (finance, human resources, marketing, and operations).

The final presentation is also a factor, as this is where the candidate demonstrates what they learned, or didn’t, through the course of the capstone.

It’s rare that an MBA candidate will fail their capstone project. After all, they’ve made it through practically an entire MBA program up until then. Even if the project is a failure from a business point of view, an MBA candidate will likely still be able to effectively analyze where and why the project failed, and what lessons can be learned from that failure going forward.

Examples of MBA Capstone Projects

Ucla anderson school of management capstone project.

The MBA program at UCLA Anderson School of Management offers three capstone options: the Global Access Program (GAP), the Business Creation Option (BCO), and Anderson Student Asset Management (ASAM).

In the GAP, students partner with high-growth global companies in a market-entry consulting project. Working in five- to six-person teams, students bid on partnership opportunities, perform five to six months of research, then travel internationally to the partner organization. Combining interviews, meetings, and research, the students develop effective strategic business plans to advance the organization’s growth, and present it to the organization’s executives, potential investors, and industry professionals.

Along the way, students are advised by faculty members who have directed, invested in, and provided consulting services to leading companies worldwide. In the last 20 years, over 3,000 students have completed the GAP, impacting 738 companies across 23 countries.

For students with an entrepreneurship focus, the BCO offers them the chance to launch a company. After taking two prerequisite courses to prepare their business plans, students will work in teams across two academic quarters. Through extensive research, development, and implementation, students will put strategies for every aspect of their business into practice. In three years, the BCO has had 47 teams and launched 24 companies.

The ASAM program is for current and aspiring quants who want experience as successful long-term portfolio managers. Guided by a faculty advisor and oversight committee, students in the ASAM program will select an optimal mix of equity, fixed income, and cash investments. Each four-member team manages approximately $200,000. Students will rotate work roles between that of an executive board member, strategy lead, risk manager, and programmer.

Carnegie Mellon University Tepper School of Business Capstone Project

The MBA program at Carnegie Mellon University Tepper School of Business offers students three different forms of capstone program: Global Study; Strategic Management of the Enterprise; and Management Game.

In the Global Study capstone, MBA students will take a four-week study abroad course in either Mainland China and Hong Kong or Germany. Previous topics of study have included bank lending in China; entrepreneurship in Asia; European economic integration; and operations management in Europe. Each class is complemented with tours of local companies and meetings with local business leaders. Upon completion of the international experience, students return to Tepper to give a final presentation.

The Strategic Management of the Enterprise capstone is an experiential learning course where students are matched with one of several consulting projects to solve business problems faced by partner companies. This is a more traditional capstone program, focused on the practical application of business skills learned through the MBA curriculum. Past clients have included Walmart, P&G, and Ameriprise.

Tepper’s Management Game capstone is an applied management experience. Student teams run a computer-simulated multinational manufacturing company for three years, acting as its executive committee. Taking place at the end of the MBA program’s curriculum, the Management Game capstone focuses on the unstructured nature of business problems and prods students to use all the functional skills they’ve learned so far. External-facing exercises include interaction with industry partners and are related to each student’s career choices.

Uniquely, the Management Game capstone is graded by external professionals on the merit of the results students deliver; students have the chance to receive direct feedback from corporate partners throughout the process.

Matt Zbrog is a writer and freelancer who has been living abroad since 2016. His nonfiction has been published by Euromaidan Press, Cirrus Gallery, and Our Thursday. Both his writing and his experience abroad are shaped by seeking out alternative lifestyles and counterculture movements, especially in developing nations. You can follow his travels through Eastern Europe and Central Asia on Instagram at @weirdviewmirror . He’s recently finished his second novel, and is in no hurry to publish it.

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capstone project in business analytics

Business Analytics

  The BSBA degree in Business Analytics, a new degree offered through the Department of Economics , provides students with the foundational education required to work in this fast-growing field of business. Students have to declare Pre-Economics BSBA as a major first and then fill out a form to declare Business Analytics after they are admitted to the College.

The raw inputs to business analytics are data from accounting, finance and marketing, as well as human resources and management in general.

Business analytics is a relatively new sub-field of data science that is informed by computer science (specifically, algorithmics, databases and programming), but also numerical methods from applied mathematics, as well as techniques from statistics and econometrics. Other subfields of data science include data mining and machine learning as well as statistics and econometrics.  Biostatistics is a subfield of data science, too, as is sports analytics.

Plan of Study

Meet the Faculty


Economics, the heart of business analytics.

How is business analytics different from most of the other subfields of data science? Business analytics is informed by theories from economics. That is, virtually every discipline in business uses basic principles from economics. At the heart of any business analytics program is substantial training in economics. Particularly important in business analytics are models of incomplete information.  For example, the models of moral hazard (where economic actors take hidden actions in their own self-interests, ones that surely are at variance with other economic actors) and adverse selection (where unobserved differences among economic actors known only privately to each result in their taking different actions) that economists have developed over the latter half of the twentieth century.  Also important are models of equilibrium strategic behavior, such as those derived in the theory of non-cooperative games of incomplete information, which allow the equilibrium features of models of moral hazard and adverse selection to be investigated.

Perhaps the best known and most successful applications of equilibrium strategic behavior in the presence of adverse selection involve models of auctions.  Auctions have garnered billions and billions of dollars for such firms as eBay and Google and have also been important in determining which firms have access to the radio spectra that make using cell phones and WiFi so convenient.  In the future, personalization on the Internet will make heavy use of models of incomplete information having private values, that is, models of adverse selection.

Business analytics is related to and borrows from econometrics.  Methods from statistics (specifically, statistical learning) are important in business analytics, too, as are methods from operations research.  In order for business analysts to be effective, they must also understand the raw materials of data science in their field, namely, accounting and financial data.

At the heart of the solution to any business problem is a decision problem.  Thus, students need to learn how to cast business problems as economic decision problems and then solve them using methods from optimization theory as well as implement those solutions on computers.  In addition, students need to be able to describe how optimal solutions are affected by changes in the environment &emdash; comparative statics.

To apply these solutions within a business environment, students need to understand methods from probability and statistics as well as computer science — specifically, computer programming and databases.

Having laid the foundations of decision theory, students then need to know how to implement decision problems using data: first, how to organize data; then how to implement business analytic methods on a computer; and, finally, how to embed decision problems in complex business environments containing incomplete information (such as those involving moral hazard or adverse selection) having equilibrium interactions.

Curricular Plan of Study

Prior to orientation or 1st day of classes : Take Math Placement Test (MPT) and place into MAC 1105.

Fall (15 hours)

Spring (15 hours)

Summer (3 hours)

Fall (16 hours)

Spring (16 hours)

Spring (13 hours)

Admission to UCF does not equate to admission to the College of Business (CoB). After receiving admission to UCF, students must qualify to be admitted to CoB and therefore all students enter the University as a ‘pre’ business major. This applies regardless of the specific business major a student intends to pursue. As a ‘pre’ business major, students will:

The above five requirements are to be completed before beginning any Business major.


All internships are now housed within the Office of Professional Development. Learn More

What can I do with this major?

General information and strategies.

Business Analytics Faculty

capstone project in business analytics

The UCI Merage School MSBA curriculum is designed to provide you with a strong foundation in modern data science to solve critical business challenges. The STEM Certified (36-month Optional Practical Training) MSBA program differentiates itself by offering flexible curricular tracks and leverages three areas of training in Data Management, Analytics Methods, and Business Context to bring a strategic advantage to businesses across all industries. Taught by world-class faculty, students will learn to extract business value in the real-world application through our industry-partnered Capstone Project.

The one-year MSBA program consists of 13 courses – eight required core courses and five electives – for a minimum of 52 units. Using three methods of training to advance students skill sets. 

MSBA Tracks

The degree incorporates flexible curricular tracks aligned with your career path in three business analytics contexts:

Within these flexible tracks, you may select electives across subject areas depending on your interests and career aspirations. 

A key component to the program is the capstone project where you engage with our industry partners to develop data-driven solutions for unique business challenges. Under the supervision of faculty and industry professionals, the capstone project provides you with the analytical tools and strategic insight to be a leader in the field.

Program Structure and Courses

Four quarter program structure.

Five Quarter Program Structure

Required Courses

BANA 200 Foundations of Business Analytics This course will provide an overview of business analytics and the theory and practice underpinnings of the MSBA curricular tracks in data analytics, marketing analytics, and operations analytics. The course will also provide the students a working knowledge of the R programming language, including a coverage of how R can be used for data visualization and graphics, data management, and basic statistics. BANA 201A Statistics for Data Science Methods of statistical inference, emphasizing applications to administrative and management decision problems. Topics: classical estimation and hypothesis testing, regression, correlation, analysis of variance, decision analysis, and forecasting. BANA 201B Management Science for Analytics An introduction to computer-based models for decision-making.  Topics include optimization (linear programming, integer programming, network flows, quadratic programming, goal programming), Monte Carlo simulation, decision analysis, and heuristics for non-convex optimization.  This course makes extensive use of optimization software, including Excel Solver and AMPL. BANA 205 Foundations of Marketing Introduction to the field of marketing. Objectives include developing familiarity with fundamental concepts, theories, and techniques in marketing, and acquainting students with the type of decisions made by marketing managers including customer targeting, product, pricing, distribution, promotion, and research. BANA 211 ProSeminar The ProSeminar courses are designed to hone career building skills, provide technology workshops and industry panel discussions, and generally prepare the students for a successful career in business analytics. During the Fall and Winter quarters, we will have guest speakers and panelists from various companies involved with business analytics, and in the Spring we focus on preparing for the CAP and aCAP certifications. BANA 212 Data and Programming for Analytics The objective of this course is to challenge and teach students how to handle data that come in a variety of forms and sizes. This course guides students through the whole data management process, from initial data acquisition to final data analysis. Topics include: Python programming, data visualization, web crawling, data manipulation and querying, and natural language processing. BANA 273 Machine Learning for Analytics Introduces methods to mine data repositories for business intelligence to facilitate analytical decision-making. Topics include clustering for market segmentation, association rules to discover relationships between different purchase decisions, Naive-Bayes classification techniques for decision making using decision-trees. BANA 277 Customer and Social Analytics Examines how to create value through web, mobile and social media analytics. Topics include: digital and social strategies; web analytics; search analytics; display and mobile advertising; social networks and social influence; social media and sentiment analysis; social media monetization; and crowdsourcing. BANA 298A Business Analytics Capstone Prep During the Winter quarter teams of up to four students will select the topic for their capstone project, conduct background research, and familiarize themselves with relevant data sets and software. BANA 298B Business Analytics Capstone Project During the Spring quarter students will do the bulk of their analysis on the capstone project, with two key deliverables due at the end of the quarter: (i) a presentation to MSBA faculty and students, and (ii) a final project report. Prerequisite: BANA 298A.

Sample Electives

Capstone Project

The Master of Science in Business Analytics program seeks to enhance in-class learning with industry practice by providing students with the opportunity to work on real-life data science problems with industry partners. The 6-month capstone project allows students to work in teams  partnering with companies to derive business value from data analytics. Advised by faculty and staff members, students run their projects from start to finish, assessing needs and devising project-specific approaches to the work.

Our Capstone Partners have included Fortune 500 companies from across the industry sector, including social media companies, major league sports teams, leading consulting firms, financial institutions, entertainment conglomerates, and more.

Our globally recognized industry partners help our students develop and showcase their knowledge of business analytics, hone their communication skills, and dive deep into the field.

Capstone Sponsor Companies:

2020 Capstone Projects

2019 Capstone Projects

2018 Capstone Projects

I chose the UCI MSBA program because of the broad range of course options. Besides studying marketing analytics, we had the opportunity to take elective courses such as natural language processing, which helped me with the ability to understand consumer attitudes and needs. Mia Zhang, MSBA '20

capstone project in business analytics

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