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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. 

• SQL. SQL is a popular coding language used in databases. Through it, analysts and developers write queries to retrieve data from transaction databases. Data scientists and data analysts also rely on the coding language. After retrieving data from the databases, business analysts present the data visually to stakeholders. 
• Statistical Languages. Working on business analytics projects will expose you to statistical languages such as R and Python. Analysts rely on R for statistical analysts and Python for programming. A combination of these languages can help you work easily with big data sets.
• Statistical Software. These projects are also quite beneficial in helping you build skills in statistical software. Through the projects, you will become familiar with SAS, SPS, and Excel. 
• Data Visualization . A significant part of business analytics involves data visualization . As part of the projects, you will not only learn how to fetch data from different databases but also present them to stakeholders. This means you will get to familiarize yourself with data visualization tools and techniques. 
• Machine Learning. As you work on the projects, you will encounter many instances where machine learning is vital . You should expect to use business intelligence tools for curating friendly user interfaces and augmented analytics to receive accurate insights. 

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

• Business Analytics Skills Practiced: Data Visualization, Machine Learning 

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

• Business Analytics Skills Practiced: Machine Learning, Data Visualization

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

• Business Analytics Skills Practiced: Machine Learning, Data Visualization, Statistical Languages

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

• Business Analytics Skills Practiced: Machine Learning

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

• Business Analytics Skills Practiced: Data Visualization 

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

• Business Analytics Skills Practiced: Data Visualization

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

• Business Analytics Skills Practiced: Machine Learning, Statistical Software, Statistical Programming

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

• Business Analytics Skills Practiced: Machine Learning, Statistical Programming

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

• Business Analytics Skills Practiced: Machine Learning, Statistical Programming 

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

• Business Analytics Skills Practiced: Data Visualization, Machine Learning

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

• Business Analytics Skills Practiced: Statistical Programming, Data Visualization

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

• Business Analytics Skills Practiced: Machine Learning, Data Analysis, Statistical Programming

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. 

• Business Analyst Template Toolkit . Whether you are a beginner or a seasoned business analyst, this template toolkit provides templates to address your needs. You will find about 12 sample templates, work samples, and guidebooks. Each of these templates can be customized to fit your needs. 
• Software Requirements Documentation Template . This template features business requirements, rules, reports, user interfaces, and data requirements. It also comes with the process flows, use cases, service level agreements, business continuities, and data security plans. 
• Attribute Metadata Template . Data features entities and attributes. Entities are identifiable classes of people or things, and attributes are characteristics that give further descriptions. You can rely on this template for the names, attributes, data types, values, and definitions of entities. You can also add extra segments like risk, priority, complexity, stability, and status. 
• Business Analysis Plan Template . This template will help you develop a reliable business analysis plan. Through this template, you can document your business planning activities regarding the project.
• Templates for Business Analysts . Tech Canvas features several business analytics templates to provide a solid structure to use in your organization. For example, they feature a strategy analysis template, solicitation and collaboration template, requirement analysis template, and Pareto analysis template. 

Next Steps: Start Organizing Your Business Analytics Portfolio

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. 

"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!"

Venus, Software Engineer at Rockbot

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. 

About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication .

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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:

• Superior academic performance in the graduate program.
• Successful completion core courses in statistical modeling and analysis, optimization, forecasting, and data mining.
• Demonstrated teamwork and problem-solving skills.

Course Deliverables:

• A formal written project report.
• A software demonstration (if developed for a particular application)
• A public presentation summarizing the project results.

There is no cost to sponsor a project.

Requirements for Sponsor

• A project lead who will interface with the student team and Faculty Coordinator on all project matters.
• 2 to 3 hours each week for meetings with the student team, either in person or online.
• A brief, well-defined problem statement. The solution to the problem must require quantitative analysis, such as statistical analysis, optimization, predictive modeling, data mining, visual analytics, and exploratory analysis.
• A prepared data set that requires data modeling, such as data cleansing, data preparation, data normalization, data merging, or data parsing. Students must be able to analyze the data using natural languages, such as R or Python.

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 organization’s business problem.
• The specific goal of the data analytics project.
• A description of the available data.
• Project-meeting schedules between the sponsoring organization and the student team.

The goal of the project is for students to:

• Understand and clearly define the business decision problem.
• Process and analyze data.
• Design, model and develop a solution.

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:

• Through August 15 in any calendar year for Fall semester.
• Through November 15 in any calendar year for Winter semester.
• First Wednesday for Fall semester.
• First Wednesday for Winter semester.
• Wednesday of the Final Examinations week for Fall semester.
• Wednesday of the Final Examinations week for Winter semester.

Capstone Projects for Winter 2023

Automated alert system for the application program interface management tool at the university of michigan.

This study presents the development of an automated mechanism for log and user affiliation change monitoring using Python scripts. The current practice of manual log queries and affiliation change observations is not only cumbersome but also poses potential security risks due to delays in observation. To address this, the proposed solution automates the process of accessing the application system and logs to generate alerts. The use of Python scripts enables efficient performance and scalability while reducing the need for manual involvement. The developed solution is expected to improve the overall security and monitoring of the system by providing real-time alerts and reducing response time.  Though, the current solution of the study is via python scripts, Splunk's built in alert system and pubsub were also thought of as alternatives but were not feasible for security concerns and lack of ability to specialize respectively.

Study of an Accessibility Tool for a Learning Management System at the University of Michigan

The University of Michigan is devoted to providing a learning environment that is comprehensively accessible, a fact exemplified by the Electronic and Information (EIT) Standard Practice Guide (SPG) of 2022. In line with the university’s accessibility goals, Information Technology Services (ITS) at the university endorsed the Universal Design Online Content Inspection Tool (UDOIT), an automated accessibility checker tool used at the university since 2019. The onset of the COVID-19 pandemic brought about pressing circumstances that halted ITS’s promotion of the tool and clouded their understanding of its usage at the university. This study leverages learning analytics to drive ITS’s assessment of the efficacy of UDOIT as an accessibility tool. It utilizes the concepts of Axiomatic System Design to systemize the design process. The study expounds the methodology used to construct a complete dataset using UDOIT output. Using a predefined set of research questions, the study conducts a full-scale analysis of the dataset, leveraging descriptive statistics with data visualization to identify patterns in the usage of UDOIT across semesters, colleges, users, and more. The study concludes with a structured summary of results and a user manual allowing ITS to replicate this analysis. Insight gained from this study will guide future UDOIT training and support ITS’s efforts towards enhancing digital accessibility at the University of Michigan.

User Behavior Analysis of Learning Management System - Pre, During and Post Covid

Canvas learning management system. The study identifies the module design and item addition patterns of faculty in Canvas and their relation to student behavior in traversing through course modules. Additionally, the study aims to determine the level of Canvas awareness among faculty and propose instructional design improvements to enhance the user experience. The analysis revealed an increase in the percentage of courses that have only the 'modules' tool enabled on the left-hand navigation during the During-Covid and Post-Covid timeline. The study also provided information on the percentage of courses in each department that used different tools during different terms. The navigational analysis of Canvas usage by learners across different academic units revealed that the School of Social Work stood out in terms of the frequency of tools accessed. Interestingly, despite the expectation that the School of Public Health would have the highest percentage of module usage due to receiving the highest level of instructional support, this was not the case. Providing instructional support can significantly enhance user engagement with Canvas. The analysis suggests that ITS teaching and learning prioritize the implementation of instructional support across all academic units to facilitate continuous user engagement with course content, as evidenced by the higher usage of the Modules tool throughout active sessions. Based on the findings, the study recommends exploring several areas for further investigation, including analyzing child tools usage, exploring the correlation between student grades and time spent on Canvas, and analyzing user navigation for external tools integrated with Canvas. These findings can help identify areas that require more instructional support to improve the user experience on Canvas.

Recent Projects

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.

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.

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.

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.

“We were impressed with the analysis and report. The results from this analysis are extremely insightful and will inform our instructional design approach and benefit the colleges we support and collaborate with.”

“The results from this analysis are extremely insightful and will be instrumental for us and the IT Accessibility Assistance Director's strategic efforts to increase and enhance adoption of UDOIT.”

“The deliverables from students’ analyses were insightful and will help us implement the automated alert system for the Application Program Interface Management tool”

College of Business Graduate Office

M.S. in Business Analytics Capstone

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:

• Define an organizational challenge.
• Collect and analyze necessary data.
• Assess possible courses of action.
• Make a recommendation to the organization.
• Present actionable insights to partners and McDonough faculty.

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.

• Capco Consulting
• Dovel Technologies
• Deloitte Consulting
• Gray Associates
• Marriott International
• The Census Bureau
• US Green Building Council
• Virtus Investment Partners

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.

• Faculty Team: Professors Sudipta Dasmohapatra and Gregory Lyon

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

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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

Mary Anderson

Search Engine Optimization Reporting Tool

Alexis Campestre

Batting Order Analysis in Major League Baseball

Northstar Athletics Item Sales Analysis

Nikki Gabrielsen

Visualizing Agricultural Data to Drive Policy

Jon Gilbert

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

Chris McLoy

Credit-bearing Internships at the University of Montana

CJ McWilliams

Small Business Online Sales Analysis

Kristi Moore

Injection Drugs in Montana

Kathryn Puczkowskyj

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

Austin Bankston

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

Jordan McNea

A New Angle on Analytics

Aspen Runkel

Scraping for Jobs: An Exploration in Data Engineering & Dashboarding

Michael Schwartz

The Yellowstone River, How Much?

Ross Stokes

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

Sarah Thompson

Analysis of Recidivism for Montana Department of Corrections

Taylor Toepke

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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.

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

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.

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

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.

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.

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

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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.

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 

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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: 

• Is Data Science Hard to Learn? (Answer: NO!)
• 15 Machine Learning Projects GitHub for Beginners in 2021
• Access Job Recommendation System Project with Source Code

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.

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.

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.

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

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.

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.

About the Author

Manika Nagpal is a versatile professional with a strong background in both Physics and Data Science. As a Senior Analyst at ProjectPro, she leverages her expertise in data science and writing to create engaging and insightful blogs that help businesses and individuals stay up-to-date with the

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Specialized Master in Business Analytics Analytics Management Capstone

The Pre-Capstone and Analytics Management Capstone courses are an experiential learning opportunity integrated throughout the SMB-A curriculum, which exposes you to leading organizations' real-world analytics challenges. You'll realize the full potential of the analytical skills acquired throughout the program, gain experience managing a small team and showcase your business expertise to a professional audience.

Connecting analytics with business

Unlike most other graduate analytics programs, Ohio State's SMB-A program is taught within the Fisher College of Business. The connection Fisher provides between business and analytics means you'll gain highly desirable real-world experience solving problems companies are facing today. No matter what stage your career is at or the analytics experience level, we tailor the program and capstone experience to you. It's time to advance your leadership skills and analytical expertise so you can reach your goals. View the three steps of the Analytics Management Capstone below.

View the SMB-A Capstone Webinar

STEP 1: SELECT YOUR REAL-WORLD PROJECT

Identify a real value-adding consulting project in diverse sectors of interest to you (technology, healthcare, operations, supply chain, education, finance, government, research, retail, etc.) , where data can inform practice. Companies all over the world and in diverse sectors choose Fisher students to take on significant problems they face.

Working professional SMB-A students (part-time or full-time) typically choose a project with analytical work related to their current employer. It's an excellent way to capitalize on existing contextual knowledge and understanding of the analysis's relevance and potential impact. It's also a great way to impress leadership at your current organization.

Being a school of business at a renowned university has its benefits. Students without a project/current employer can work with a SMB-A program director to tap into Fisher sourced-projects for clients who expect the same quality of deliverables and positive teamwork that they would receive from their own employees.

Examples of Past Projects

Sample of participating organizations.

As an SMB-A student, you'll benefit from the unique combination of a tight-knit graduate program at one of the largest universities in the country. Ohio State's Fisher College of Business has a wide range of organizations that work with our SMB-A and MBA graduate students on analytics projects.

ARE YOU AN ORGANIZATION LOOKING TO PARTICIPATE?

Having analytical work completed by Fisher College of Business students is a great way to contribute while also benefitting your organization. Fisher has numerous project opportunities in both the undergraduate and graduate analytics curricula that can fit your needs and interest. Accepted projects typically require organizations to provide data relevant to the context. They will also require time allocated to dialogue between the originating organization and the student/team to ensure a contextual understanding of the data set's task and nature.  To facilitate the best match between your project and student availability, please complete this form .

Connect with Fisher about analytics projects

STEP 2: LEVERAGE YOUR ANALYTICS MICRO-TEAM

As part of your capstone experience, you and another SMB-A student manage a small analytics team in a real-world setting, which occurs in a spring Pre-Capstone course.

ABOUT THE PRE-CAPSTONE:

The Pre-Capstone is a data and methods preparatory curriculum in advance of the summer term. This curriculum continues discussions of problem structuring, begun in the Fall. It includes a 10-week Micro-Team experience where SMB-A students manage and collaborate with a junior analyst and advisory faculty member. By its design, and exposure to additional analytics tools, the Pre-Cap ensures you'll be well-prepared for successful independent Capstone work in the Summer term. A typical team is as follows:

* The number of assigned Fisher undergrad students matches the number of SMB-A students on the micro-team (1-1, 2-2, 3-3).

SOME BENEFITS OF THE MICRO-TEAM EXPERIENCE:

• Demonstrate skills gained in coursework as a project lead
• Establish tasks and timelines
• Coordinate any required NDAs
• Apply descriptive/predictive/prescriptive analysis
• Reporting and presentation work that builds leadership

STEP 3: PUT THEORY INTO PRACTICE

To help guide initial thoughts and the ultimate development of the project and its deliverables, SMB-A students and their teams will make use of several frameworks. Examples include the OUtCoMES Cycle, Systems-Oriented A3, and the Management Analytics Decision-Tree. These resources, and more, are introduced and utilized during 1-hour advisory sessions every two weeks during the autumn and spring semesters, which lead into the summer when you will move to two 1-hour advisory sessions every week for seven weeks. Below is a quick look at the Management Analytics Capstone timeline. The capstone is an integral part of the SMB-A program structure and curriculum .

Project Planning Resource Examples

An iterative process used to structure otherwise unstructured or poorly structured real-world problems. The approach identifies core performance objectives, critical levers, and salient limitations on managerial decision-making. Used with analytical tactics, the approach provides actionable prescriptions to practice. Learn more about The OUtCoMES Cycle.

To support documentation throughout the OUtCoMES Cycle and assist in the final capstone presentation, students and their teams complete both a preliminary A3 for early feedback on project plans and a final A3 as part of your final project report. No matter your analytics experience level, Fisher teaches proven real-world business-analytics techniques and provides high-value resources to support your development and career growth.

To help you think about the analytical tools and tactics that might prove useful in each stage of your project journey, the International Institute for Analytics provides a decision-tree framework.  This framework can guide you in selecting analytical approaches from descriptive, to predictive and through prescriptive stages of your work. In the SMB-A program, you'll gain an understanding of multiple vantage points through which data is considered, extracted, and scrutinized to empower you as a decisive business leader capable of leading analytics teams.

Next, explore the SMB-A program structure

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Business Capstone Projects: Format & Examples

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Key Characteristics

• Integration of Business Concepts: The project typically requires students to synthesize knowledge gained from various business disciplines such as finance, marketing, management, operations, and strategy.
• Real-World Application: Business capstone projects often involve addressing real-world business challenges or opportunities. Students may work with actual companies, analyze case studies, or propose solutions to current business issues.
• Interdisciplinary Approach: Capstone projects may encourage an interdisciplinary approach, allowing students to draw upon insights from multiple business areas to propose holistic solutions.
• Research and Analysis: Students are expected to conduct thorough research, gather relevant data, and analyze information to support their recommendations or findings.
• Strategic Decision-Making: Many business capstone projects focus on strategic decision-making. This involves proposing strategic initiatives, business plans, or operational improvements.
• Presentation and Communication Skills: Students are often required to present their findings and recommendations to a panel of faculty members, industry professionals, or both. This enhances their ability to communicate complex business ideas effectively.
• Team Collaboration: Some capstone projects are collaborative, requiring students to work in teams. This mirrors the teamwork often required in professional business settings.
• Professional Development: Capstone projects may contribute to students’ professional development by exposing them to the complexities of the business world and requiring them to think critically about business challenges.

The specific nature and requirements of a business capstone project can vary between educational institutions and degree programs. However, the overarching goal is to provide students with a practical and meaningful experience that prepares them for the challenges and complexities of the business world.

Business Capstone Project Format

• Title Page:  Includes the title of the capstone project, student’s name, academic institution, department, date of submission, and any other required details.
• Executive Summary:  Provides a concise overview of the entire capstone project, summarizing key objectives, methods, findings, and recommendations.
• Table of Contents:  Lists the main sections, subsections, and corresponding page numbers to facilitate easy navigation.
• Introduces the business problem or opportunity addressed by the project.
• States the purpose, significance, and objectives of the capstone project.
• Summarizes relevant literature related to the business problem or opportunity, incorporating academic and industry sources.
• Highlights existing theories, research findings, and industry best practices.
• Highlights gaps in current knowledge and sets the theoretical foundation for the project.
• Describes the research design, data collection methods, and any analytical tools or techniques used i.e. SWOT , PESTLE , porter’s five forces .
• Discusses the sample population, sampling methods, and ethical considerations.
• Presents the findings of the data analysis or the outcomes of project implementation.
• Includes tables, charts, graphs, or other visual aids
• Interprets the significance of the findings in the context of the literature review and theoretical framework.
• Discusses implications, limitations, and potential areas for future research.
• Addresses any limitations of the study and suggests areas for future research or business strategy.
• Summarizes the key findings and their implications.
• Restates the project’s objectives and how they were achieved.
• Offers final thoughts on the business problem or opportunity.
• Provides actionable recommendations based on the research findings.
• Offers strategic suggestions for addressing the business challenge or maximizing the identified opportunity.
• May include opportunities for further research.
• If applicable, outlines a detailed plan for implementing the proposed recommendations.
• Considers timelines, resource requirements, and potential challenges.
• References:  Lists all sources cited in the capstone project following a specific citation style (e.g., APA, MLA).
• Appendices: Includes additional materials, such as surveys, interview transcripts, financial statements, or any supplementary information that supports the project.

It’s essential to adhere to any specific formatting guidelines provided by the educational institution or program. Additionally, the content and structure of a business capstone project may be influenced by the nature of the project (e.g., case analysis , strategic plan, research study) and the academic level (undergraduate or graduate).

Business Capstone Projects Examples

• Supply Chain Optimization: Analyzing and optimizing the supply chain processes of a company to enhance efficiency, reduce costs, and improve overall logistics.
• E-commerce Strategy Development: Creating a strategic plan for a traditional brick-and-mortar business to transition into e-commerce, considering online marketing, website development, and digital customer experience.
• Employee Engagement Program: Designing and implementing an employee engagement program to improve workplace satisfaction, productivity, and retention.
• Sustainable Business Practices: Developing a sustainability strategy for a business, incorporating environmentally friendly practices, ethical sourcing, and social responsibility.
• Data Analytics Implementation: Proposing and implementing a data analytics strategy to extract meaningful insights from business data, aiding in decision-making and performance improvement.
• Brand Revitalization Campaign: Creating a comprehensive plan to revitalize a struggling brand, including rebranding, marketing strategies, and customer engagement initiatives.
• Risk Management Framework: Developing a risk management framework for a business, identifying potential risks, and providing strategies to mitigate and manage these risks effectively.
• Customer Relationship Management (CRM) Implementation: Implementing a CRM system for a company to enhance customer relationships, streamline communication, and improve customer satisfaction.
• International Marketing Plan: Creating an international marketing plan for a product or service, considering cultural nuances, market trends, and global competition.
• Corporate Diversity and Inclusion Program: Designing and implementing a diversity and inclusion program to foster an inclusive workplace culture, attract diverse talent, and promote equity within the organization.
• Strategic Business Plan: Developing a comprehensive business plan for a startup or an existing business, addressing aspects such as market analysis, financial projections, and operational strategies.
• Market Entry Strategy: Analyzing and proposing a market entry strategy for a company looking to expand into a new geographic area or target demographic.
• Operational Efficiency Improvement: Identifying inefficiencies in a company’s operations and proposing strategies for improvement in areas such as supply chain management, production processes, or customer service.
• Financial Analysis and Investment Recommendation: Conducting a thorough financial analysis of a company and providing investment recommendations based on factors such as financial performance, industry trends, and risk assessment.
• Corporate Social Responsibility (CSR) Initiative: Designing and proposing a CSR initiative for a company, taking into consideration ethical considerations and social impact.
• Product Launch Strategy: Developing a strategic plan for the launch of a new product, including market positioning, pricing strategy, and promotional activities.
• Mergers and Acquisitions (M&A) Analysis: Analyzing the potential benefits and risks of a merger or acquisition and providing recommendations on whether to proceed.
• Digital Transformation Plan: Proposing a digital transformation plan for a traditional business to enhance its technological capabilities and competitiveness in the digital era.
• International Business Expansion: Developing a plan for expanding a business internationally, considering factors such as cultural differences, regulatory requirements, and market potential.
• Entrepreneurial Venture Proposal: Creating a comprehensive proposal for a new entrepreneurial venture, including a detailed business model, financial projections, and growth strategies.
• Franchise Expansion Strategy: Developing a strategic plan for a successful business to expand through franchising, including market analysis, franchisee selection criteria, and operational guidelines.
• Economic Impact Assessment: Conducting an economic impact assessment for a proposed business development project, considering factors such as job creation, community benefits, and potential challenges.
• Blockchain Integration for Business: Proposing and implementing a strategy for integrating blockchain technology into business processes, enhancing security, transparency, and efficiency.
• Strategic Human Resources Management: Designing and implementing a strategic human resources plan to attract, develop, and retain talent in alignment with the company’s overall objectives.
• Customer Loyalty Program Design: Creating a customer loyalty program to increase customer retention, improve brand loyalty, and drive repeat business.
• Digital Marketing Campaign Analysis: Conducting a comprehensive analysis of a company’s past digital marketing campaigns, identifying strengths and weaknesses, and proposing strategies for improvement.
• Global Risk Assessment: Evaluating the global business environment to assess potential geopolitical, economic, and regulatory risks, and proposing risk mitigation strategies for international operations.
• Smart Technology Integration: Developing a plan for integrating smart technologies (IoT, AI, etc.) into business operations to improve efficiency, innovation, and competitiveness.
• Strategic Partnership Development: Identifying and evaluating potential strategic partnerships for a business, including collaborations, joint ventures, or alliances to drive growth and mutual benefits.
• Corporate Crisis Management Plan: Creating a crisis management plan for a business, outlining communication strategies, risk mitigation protocols, and recovery plans in response to unforeseen events.

In conclusion, the key to success in a business capstone project is a combination of strategic thinking, thorough research, effective collaboration, and clear communication. Success is achieved by addressing real-world business challenges, proposing innovative solutions, and demonstrating a deep understanding of business concepts.

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Business Statistics and Analysis Capstone

dennislamcv1/RiceUBusinessStatistics

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About this Course

The Business Statistics and Analysis Capstone is an opportunity to apply various skills developed across the four courses in the specialization to a real life data. The Capstone, in collaboration with an industry partner uses publicly available ‘Housing Data’ to pose various questions typically a client would pose to a data analyst.

Your job is to do the relevant statistical analysis and report your findings in response to the questions in a way that anyone can understand. Please remember that this is a Capstone, and has a degree of difficulty/ambiguity higher than the previous four courses. The aim being to mimic a real life application as close as possible.

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