business analyst projects for resume

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

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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  

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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?

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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

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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

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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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Table of Contents

• Why are Business Analytics Projects Important?

List of Business Analytics Projects [Based on Levels]

Top 10 business analytics project ideas, business analytics projects for beginners, business analytics project ideas for mba students, business analytics project topics for intermediate, key tools for business analytics project, are business analytics projects difficult to complete, final thoughts.

As a beginner in business management, one of the most crucial skills is gathering and analyzing data to make informed decisions. Business analytics uses data and statistical methods to extract insights and make data-driven decisions. The good news is that there are countless business analytics project ideas that you can start working on to improve your skills and help your business thrive. This blog will explore the top 10 business analytics projects you can do online as a beginner or an experienced professional. So, let’s dive in and discover how you can use business analytics projects to gain a competitive advantage in today’s fast-paced business world.

Why are Business Analytics Projects Important?

Business analytics is an amalgamation of business management and data analytics. High-value projects aimed at business development add value to the profile or resume of candidates who opt for a business analytics career. Business analytics projects are important because they enable data-driven decision-making, helping businesses uncover valuable insights from their data. These projects optimize operations, identify growth opportunities, and enhance overall efficiency, leading to improved profitability and competitiveness. Moreover, they provide a foundation for predictive and prescriptive analytics, enabling organizations to proactively address challenges and capitalize on emerging trends.

Here is a list of business analytics projects based on levels of experience:

Business Analytics Project Ideas: 

• Sales Data Analysis
• Customer Review Sentiment Analysis
• Market Basket Analysis
• Price Optimization
• Stock Market Data Analysis
• Customer Segmentation
• Fraud Detection
• Equity Research
• Social Media Reputation Monitoring
• Real-Time Pollution Analysis

Business Analytics Project Ideas for Beginners: 

• Employee Attrition and Performance
• Prediction of Sales in Tourism for the Next Five Years
• Prediction of the Success of an Upcoming Movie
• Prediction of the Fate of a Loan Application

Business Analytics Projects for Intermediates: 

• Creating Product Bundles
• Life Expectancy Analysis
• Building a BI app

Business Analytics Projects Topics for MBA Students

• Predicting Customer Churn Rate
• Prediction of Selling Prices for Different Products
• Store Sales Prediction

Here are the top 10 projects in business analytics, each offering unique insights and opportunities for data-driven decision-making in various industries. 

1. Sales Data Analysis 

It involves the analysis of data on every aspect of a company’s sales. It determines the total number of sales, average monthly sales, demographics of customers, and patterns of selling periods. It allows the company to make informed decisions to prioritize the production of specific products and scale them. To analyze the sales data, students can use different tools and languages. Students can use SQL to extract data from the database. Excel or Google Sheets can clean and analyze data for charts and graphs. For advanced visualizations and dashboards, Tableau or Power BI can be used. Python or R is good for advanced data analysis and statistical modeling, like looking for trends or making predictions.

• Sales Analysis Source Code  

2. Customer Review Sentiment Analysis

It is the process of determining the emotional state of customers after they purchase or use the products. It allows the company to realize the possible reasons for customer complaints and measures to improve the features and quality. Students can use Python or R for data analysis. Tools like TextBlob and NLTK for sentiment analysis.

• Reviews Sentiment Source Code

3. Market Basket Analysis 

It involves the analysis of the correlation between the ales of different products when combined. It helps improve the business by identifying the best combinations and increasing the preferences of customers for the products. For this project, students can analyze data using the Apriori algorithm. They can use either Python or R programming languages.

• Market Basket Analysis Source Code

4. Price Optimization 

It involves investigating historical prices, crucial price factors, the markets where the company operates (and their economic contexts), the profiles of potential clients, etc. Programming Languages like Python or R are suitable for this project. Regression analysis and demand forecasting models are used to analyze the data.

• Tensor House Source Code

5. Stock Market Data Analysis

The project involves determining the frequency of rise and fall in price, the general trend of average monthly closing prices over the year, and trading volumes. Candidates can select a specific dataset and explore the company’s stock performance history. To analyze the data for this project, Python and R is used. Tools like Pandas and Numpy are used for manipulating the data.

• Stock Market and Analysis Source Code

6. Customer Segmentation

It refers to categorizing a company’s clients into different groups based on their purchasing behavior, financial level, interests, needs, and loyalty to the business. It helps optimize marketing campaigns and maximize the profits from each client. The K-means and Hierarchical clustering algorithms are generally used for this project.

• Customer Segmentation Source Code

7. Fraud Detection

Credit card fraud, identity theft, and cyber-attack are common fraudster challenges faced across various industries. Projects on fraud detection involve choosing a dataset and running statistical analyses to identify fraudulent operations. Machine learning algorithms such as decision trees and logistic regression are used for fraud detection.

• Fraud Detection Source Code  

8. Equity Research

Equity is the value of the returns received by a company’s shareholders after liquidating all the assets and clearance debts incurred by the company. Equity research plays a crucial role in the successful run of both shareholders and companies. Students can use Excel and Python to analyze the financial datasets for this project. Tools such as ratio analysis and financial statement analysis are in equity research.

• Equity Research Source Code

9. Social Media Reputation Monitoring

It is the process of gauging the presence and influence of a brand on customers through social media. Using analytical tools and techniques, the project audits, monitors, and interprets social media users’ opinions about the products. It helps revise social media marketing strategies to promote the business. Social media monitoring tools such as Hootsuite and Sprout Social are used to analyze the data.

• Social media reputation monitoring

10. Real-Time Pollution Analysis

It is a typical data visualization project, allowing the candidates to learn univariate and multivariate data analysis. The methodology can be reproducible to business aspects. Students can use either Python or R to build the project. Matplotlib or Plotly are used for creating visualizations.

• Air Pollution Tracker Source Code

Graduates from several fields, including engineering, with an inclination for business, choose management as their career path. Business Management for beginners , augmented with business analytics projects, provide potential platforms to lay a strong foundation to build their career. The following are the most-edifying sample business analytics projects for students.

1. Employee Attrition and Performance

These projects are ideal for acquiring the qualitative analysis skills of employee attrition to find answers for the event’s who, when, and why. They also predict quantitative aspects of human resource dynamics for the organization’s next 5 to 10 years. The balance between attrition and retention is the secret to optimal human resources and talent utilization. To do this, students can use Excel to clean the data. SQL is used for data extraction. Python or R for data analysis.

• Employee Attrition Performance Source Code  

2. Prediction of Sales in Tourism for the Next Five Years

This project helps business analysts to improve their skills in applying data mining to determine patterns and correlations among tourism packages and their preferences. It has two approaches: qualitative and quantitative. Both approaches help beginners to hone their analytical and judgmental skills. To predict sales, statistical analysis tools like R or Python are used. Excel and SQL are used for cleaning and extracting data, respectively.

3. Prediction of the Success of an Upcoming Movie 

Business management professionals have a good scope in the film industry as numerous films enter the screen. These projects involve forecasting success based on the analysis of variables, including genre, language, directors, actors, actresses, budget, locations, etc. The prediction depends on the model devised based on the data of predetermined variables associated with previously released movies against their success. Like the other projects, students can use Python or R to predict the success of the upcoming movie.

4. Prediction of the Fate of a Loan Application 

These projects expose beginners to several machine-learning tools and techniques, and datasets. They also introduce the candidates to various parameters and help them gain the ability to recognize variables under eccentric circumstances. The top 3 machine-learning solution approaches for loan prediction are as follows.

• Support vector machine 
• Random forest

Pandas are the most straightforward and powerful Python libraries for beginners used for the prediction of the fate of loan applications.

ECBA certificate training is among the best options to improve the profile of business analytics aspirants. A merit of this program is the opportunities for business analytics projects for MBA students. Three top business analytics project ideas are as follows.

1. Predicting Customer Churn Rate

It involves predicting the decline of customer rates. It has scope for stakeholders to identify setbacks in the business. It helps learn several statistical tools, such as SHAP (Shapley Additive exPlanations), RandomSearch, and GridSearch, for univariate and multivariate analysis on a retrieved dataset.

• Customer Churn Analysis Source Code

2. Prediction of Selling Prices for Different Products

It refers to the determination of the price of a product that attracts customers with an optimal profit margin. Further, it also helps companies to determine the offers to improve business. These projects help acquire skills to employ machine learning algorithms like Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks that use different metrics to test each of their performances.

3. Store Sales Prediction

These projects involve working with numeric and categorical feature variables and performing univariate & bivariate analysis to find the redundancy in variables associated with the store chain of a company. They help the candidates learn machine learning models such as the ARIMA time series model. 

• Store Item Demand Forecasting Source Code

Business analytics project ideas for experienced professionals should involve a complex combination of statistical parameters and real-world scenarios to enhance their skills significantly. Following are the business analytics project examples suitable for the intermediate levels.

1. Creating Product Bundles

It is a method that combines different products from the same company and sells them as a single unit. Under these projects, candidates learn market basket analysis and time series clustering methods to identify product bundles using sales data.

Here is the Product Bundle Source Code  

2. Life Expectancy Analysis

These projects aim to determine the monetary value of the potential consumer of the products and services of a company. Traditionally, government organizations utilize life expectancy analysis to determine the correlation between life expectancy and a nation’s GDP.

• Life Expectancy Analysis Source Code  

3. Building a BI app 

Business intelligence apps or tools play a critical role in finding urgent solutions to issues that are high for the business. Low to no-code custom apps for decision-making and long-term strategies are invaluable for an organization.

Here is the Business Intelligence Analysis Source Code  

Here is a list of top tools that are required business analytics projects: 

• Data Visualization Tools (e.g., Microsoft Power BI, Looker) 
• ETL/ELT Tools
• Data Warehousing (e.g., Amazon Redshift, Google BigQuery, etc.)
• Data Analysis and Manipulation Tools
• Data Mining and Machine Learning Tools (e.g., Scikit-learn, RapidMiner)
• Data Quality Management Tools
• Data Integration Tools
• BI Suites 
• Data Catalog Tools (e.g., Collibra)

Business analytic projects face several challenges that hamper their successful implementation. Technological advancement expands the options for tools and techniques. Still, they create a grey zone wherein the new tools emerge with overlapping functionalities interfering with decision-making. Other reasons for the failure of business analytics projects are: 

• Lack of well-defined and explicit goals 
• Poor data integration 
• Lack of conversion of insights and outcomes into actions.
• Poor adaptations to the ongoing development

Business analytics is blooming parallel to technological advancements, and every business is leveraging analytical tools and techniques to optimize its actions. Whether experienced or fresher, diverse business analyst projects for resume help you upgrade your profile. KnowledgeHut Business Management for beginners is highly recommendable for a firm foundation before undertaking business analytics projects, as it provides top-quality augmentation to your aptitude for the discipline.

Frequently Asked Questions (FAQs)

1. what are some common challenges faced in business analytics projects.

The common challenges faced in business analytics projects are: 

• Changing requirements or business needs 
• Conflicts with stakeholders 
• Poorly documented processes 
• Unrealistic timelines.

2. What is predictive analysis, and how is it used in business analytics projects?

Predictive analytics is a branch of analytics that predicts future outcomes using models based on historical data. Businesses use customer data and transaction information to predict the performance of the products and make strategies to optimize profits. 

3. What are some popular business analytics tools used in business analytics projects?

Popular business analytics tools are SAS business analytics, Sisense, Microstrategy, KNIMETIBCO Spotfire, Tableau big data analytics, Power BI, and Excel.

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7 Best Business Analytics Projects for Your Resume (Updated for 2024)

Introduction.

Expected to exceed $23 billion in 2032, analytics as a service (AaaS) and business analysis are essentially about extracting patterns—and ultimately monetary value—from user data. As a skilled business analyst, your job is to improve decision-making, analyze new products, enhance customer experience, optimize processes, and manage risk in more sensitive cases.

When approaching a business analytics interview, you must recognize that your responsibilities will include understanding the business, identifying requirements, communicating, and sometimes, making presentations and managing.

These responsibilities are only given to candidates who demonstrate competence with existing business analytics projects.

However, we understand how challenging it is to find and get started on an analysis project to add to your resume. So, we’ve done the hard part for you.

We’ve compiled the 5 best business analytics projects with the most detailed and realistic datasets.

Market Basket Analysis

What is this project about.

Cross-selling and upselling are powerful tools used in retail to maximize sales potential and increase customer lifetime value. Market basket analysis strives to identify distinct patterns of items frequently purchased together.

Retail companies, such as Target and Best Buy, and e-commerce industries, like Amazon, often apply this type of analysis.

This particular project uses Instacart’s anonymized data on customer orders over time to allow you to predict which previously purchased products will be in a user’s next order.

The project involves taking account of customer demographics, order history, and product information to build a machine-learning model that accurately predicts patterns.

As a business analyst, you aim to optimize the company’s revenue and profit potential. For example, you might identify that customers often purchase butter and bread together. With this insight, the store could place these items together or offer bundle discounts to increase sales.

Further, by analyzing which products are often bought together, the store can optimize inventory levels and product placement to ensure availability and minimize stockouts.

Why is it a must for your resume?

Successful completion of the project will highlight your proficiency in data manipulation, advanced data mining, and data visualization techniques. The specific skills will depend on your chosen tools, but SQL, pandas, Apriori, and Power BI/Tableau will likely be involved.

Mastering these skills is essential for extracting valuable insights from data, which can then be applied to enhance product placement, promotions, and overall sales—all outcomes that companies like Amazon and Best Buy highly value.

Sales Forecasting with Python

Sales forecasting leverages past sales data, market trends, and economic indicators to estimate future sales for a specific period, such as a month, quarter, or year.

Accurate sales forecasting can help businesses make better profits, optimize resource allocation, improve inventory management, and set realistic sales targets.

This Python project dataset , sourced from a retail store, expects you to build and evaluate models to predict national store sales by holidays and department, focusing mainly on the seasonal nature of the business.

An example of the project’s significance could involve an automotive company like Ford, which can successfully leverage sales forecasting to predict future demand for a particular car model, optimizing production schedules and reducing unsold units.

Another industry where sales forecasting is heavily used is insurance sales forecasting, where companies promote insurance policies based on demographic trends, the economy, and regulatory changes.

For instance, favorable regulatory changes can cause an upsurge in young drivers, which may increase car insurance sales.

As sales forecasting is key to every industry, finding room for this project in your resume can prove significant.

This project allows you to showcase expertise in time series analysis and forecasting using statistical models, such as ARIMA and machine learning.

It highlights your ability to transform historical data into accurate predictions, improving business efficiency and decision-making. This skill set is highly valuable for roles requiring strategic forecasting and analysis throughout the market.

Sentiment Analysis of Customer Reviews

Understanding human sentiments is critical to industries that rely heavily on customer feedback, preferences, and behavior to recommend products or improve their services.

Sentiment Analysis of Customer Reviews focuses on determining the emotional tone behind text using natural language processing, whether positive, negative, or neutral.

This project utilizes user ratings for various products to create a model to suggest items to users based on their purchase history and preferences. You’re expected to build a model using item-to-item collaborative filtering, a technique commonly used by e-commerce platforms like Amazon.

Apart from the example cited by Amazon on the business analytics project, you could consider a telecommunication company, such as Verizon. They might segment the customers based on their usage and satisfaction patterns to recommend personalized offers.

Social media platforms like Facebook or Twitter also use sentiment analysis to track public opinion on various topics, including brands, products, and events. This gives them leverage to recommend relevant content.

Sentiment analysis is essential in customer-facing products such as Netflix, Spotify, and YouTube that strive to deliver personalized feeds to cater to each user.

This project showcases your text mining, web scraping, and data processing skills with Python and pandas, along with expertise in machine learning for natural language processing.

It also allows you to demonstrate your ability to manage unstructured data from various sources, extract insights, and provide actionable recommendations.

Price Optimization Analysis

Pricing is a considerable factor in today’s competitive markets with global players. Price optimization analytics uses data and analytical techniques to identify a model that dynamically adjusts the price of a product to maximize revenue and profit.

This ClearSpark takehome challenge expects you to create a recommendation engine that involves handling missing values, processing data for analysis, understanding patterns, and building a recommendation model to facilitate the recommendation algorithms.

One of the most prominent use cases of price optimization involves ride-sharing companies such as Uber and Lyft. They use dynamic pricing models to adjust fares based on demand, traffic, and supply.

Retailers like Amazon and Walmart also leverage vast amounts of data to adjust product prices in real time.

Airlines, for instance, dynamically adjust ticket prices based on factors like booking time, demand, competition, and fuel costs.

Price optimization analytics uses regression analysis to study historical data and understand pricing patterns. This project shows your ability to perform detailed analysis and model pricing scenarios, combining analytical skills with business understanding.

It also demonstrates your ability to use data to influence decision-making, including setting prices based on customer segments and planning promotions. Tech companies and industries focusing on pricing strategies value this experience, as it helps maximize revenue and profitability.

Life Expectation Analysis

Life expectancy analysis is about studying and interpreting data related to the average lifespan of a population. By examining age, race, sex, income, education, access to healthcare, and various other factors, analysts can design models that can accurately describe the life expectancy of a demographic.

This project , while not directly correlating with business analytics, has you identify key factors influencing life expectancy, clean data, build statistical models, and evaluate the performance of the ML models. Data visualization of the outcomes can also significantly enhance your resume.

Life expectancy analysis’s most substantive industrial use revolves around determining insurance premiums and performing risk calculations against health insurance policy applications. Other examples include identifying potential target populations for new drugs and detecting regional and global health trends.

Apart from direct healthcare, non-profit organizations, and epidemiological studies may employ life expectancy analysis to identify areas of interest.

Completing this project showcases your skill in handling diverse datasets from various sources, such as mortality rates, health indicators, and demographics. It highlights your expertise in statistics and domain-specific models to analyze data, identify trends, and draw meaningful conclusions.

Moreover, it demonstrates your proficiency in data exploration, regression analysis, and predictive modeling, making you a valuable asset for strategic planning and policy-making through data-driven insights.

Resume Screening

This project involves analyzing resumes to identify patterns and trends in the skills and qualifications of individuals across various fields. By examining the resumes’ content, such as skills, education, and experience, we aim to categorize them into specific professional domains. The goal is to develop a model that automatically classifies resumes into categories like Data Science, Web Development, HR, etc.

The dataset provides textual data extracted from resumes along with their associated categories. This project challenges you to perform text preprocessing and feature extraction and build machine-learning models for text classification. Additionally, visualization of insights from this data can enrich your portfolio and highlight your analytical capabilities.

An industrial application of resume classification is in automating candidate shortlisting for recruitment. Companies can use similar models to filter resumes based on predefined job roles or categories, saving time and improving efficiency. Additionally, these models can be used to analyze market trends in skills demand and identify gaps in workforce capabilities.

Completing this project demonstrates your expertise in natural language processing (NLP), text data preprocessing, and machine learning for classification tasks. It highlights your ability to handle unstructured data, extract meaningful features, and build predictive models.

Moreover, this project showcases your text analytics, visualization, and practical problem-solving skills, making you a standout candidate for roles involving data science, machine learning, or talent analytics.

Predicting Market Capitalization

This project analyzes McDonald’s financial performance over time using its financial statements. By examining key metrics such as revenue, earnings, market cap, and various financial ratios, we aim to uncover trends, patterns, and insights that can inform investment decisions and strategic planning. The dataset includes financial data for McDonald’s over 21 years, featuring details like operating margins, dividend yields, and total liabilities.

The dataset offers comprehensive financial information, providing an opportunity to perform time-series analysis, visualize trends, and create models to predict future financial performance. Additionally, it includes insightful metrics like the P/E ratio and dividend yield, which are crucial for evaluating company health and shareholder value.

This analysis could be an industrial application in building financial forecasting models to guide corporate decision-making. For instance, analysts could use similar data to predict earnings growth or evaluate how changes in market conditions impact financial metrics like operating margins or cash on hand. These insights are vital for stakeholders, including investors and executives, to make informed decisions.

Completing this project demonstrates your expertise in financial data analysis, time-series modeling, and visualization techniques. It showcases your ability to interpret and analyze structured datasets, draw meaningful conclusions, and present findings effectively.

Moreover, this project highlights your skills in financial modeling, strategic planning, and creating predictive insights, making you a strong candidate for financial analysis, corporate strategy, or data-driven investment consulting roles.

Tips to Add More Business Analyst Projects to Your Resume

If you’re interested in expanding your resume with more business analytics projects or seeking machine learning project ideas , check out our articles. Still, if you can’t find a project that fits your interests, don’t hesitate to create your own, following the tips below:

Find Interesting Business Analyst Projects

Don’t stop at online projects!

Identify a question or problem you’re passionate about solving that addresses a common business need, possibly in the particular company you’re interested in.

By pursuing and completing a project relevant to a company’s challenges, you demonstrate how your skills are applicable in real-world scenarios, making your skills more relevant to potential employers.

Come Up with Creative Solutions

Once you’ve decided on a problem, think creatively about how to solve it. The project should highlight your unique approach and analytical skills. The more innovative your solution, the more likely it is to grab an employer’s attention.

For example, if you’re interested in real estate, you might consider projects to help a company decide which city to expand into by analyzing market demand, property prices, rental yields, and economic conditions.

Practice Takehome Projects

If you need more practice, we offer takehome projects that allow you to tackle real-world problems and sharpen your analytics, machine learning, and statistics skills.

Take on Volunteer Projects

Another great way to build your portfolio is by taking on volunteer projects. Non-profits and small businesses often need help with data analysis but don’t have the resources to hire full-time business analysts. You gain valuable experience and help a good cause by offering your skills.

The Bottom Line

And there you have it—the top 5 business analytics projects you can use to highlight your skills and boost your resume. Remember, every project you take on brings you one step closer to mastering the skills top employers seek. Showcasing these projects can set you apart in today’s competitive job market.

Table of Contents

Why are business analysis projects important, key tools required for business analysis projects, top challenges in business analysis  projects, 10 business analysis project ideas, conclusion , top business analysis projects for 2024.

Business Analytics is a highly promising field crucial for planning and decision-making in large organizations. Given its significant impact on the market, there is a high demand for professionals, resulting in numerous job opportunities. To secure these positions, having a compelling resume is essential. An effective way to enhance your resume is to showcase the business analytics projects you have undertaken. 

In this article, we'll discuss why business analytics projects matter, check out the tools you need, discuss the challenges, and share the 10 best projects to supercharge your resume.

Business analytics projects are important for two key reasons. 

• They provide a practical way to apply various skills to real-world challenges from start to finish. While different exercises are helpful, working on complete projects allows for comprehensively applying various skills. 
• A portfolio featuring these projects is crucial for landing a business analyst job. Beyond an impressive resume and list of qualifications, employers want to see your skills in action. A portfolio filled with completed projects is the best way to demonstrate what you can do and increase your chances of securing interviews effectively.

Here are the key tools required for successful business analytics projects, each serving a specific purpose in the analytical process:

Data Analysis Tools

Tools like Excel, Power BI , Tableau , SQL , and Python are crucial for collecting, organizing, and interpreting data from various sources in business analytics projects. They help identify patterns, trends, and opportunities in data, allowing for hypothesis testing and assumption validation.

Process Modeling Tools

In business analytics projects, tools like Visio, Lucidchart, Bizagi, BPMN, and UML assist in documenting and optimizing analytical processes. These tools use graphical notations and diagrams to capture the current and desired states of processes, facilitating effective communication with stakeholders.

Requirements Management Tools

Jira, Trello, Confluence, Rational RequisitePro, and Caliber are examples of tools that help manage requirements for business analytics projects. They ensure clarity, completeness, and consistency in aligning requirements with project goals and stakeholder needs.

Collaboration Tools

Collaboration tools such as Slack, Zoom, Teams, Google Workspace, and SharePoint are instrumental in promoting communication and teamwork among analysts and stakeholders, especially when working across different locations and time zones.

Testing Tools

Testing tools, including Selenium , TestRail, Postman, SoapUI, and JMeter, play a crucial role in verifying and validating the quality and functionality of solutions or products in business analytics projects. They assist in designing, executing, and reporting test cases while identifying and resolving defects and issues.

Change Management Tools

Change management tools like Prosci ADKAR, Kotter's 8-Step Model, Lewin's Change Model, and Change Compass help plan, implement, and evaluate changes within the context of business analytics projects. These tools assist in assessing the impact and readiness of change and managing resistance and associated risks.

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Getting business analytics projects right involves recognizing and addressing key challenges. Let's delve into two major aspects:

Technological Complexity

Navigating the ever-evolving technological landscape poses a significant challenge for business analytics projects. The abundance of tools and techniques brings opportunities, but the risk of overlapping functionalities can complicate decision-making processes.

Project Execution and Adaptation

The success of business analytics projects hinges on overcoming challenges related to setting clear goals, integrating data seamlessly, and translating insights into actionable strategies. Furthermore, adapting to ongoing development processes is crucial for ensuring the project aligns with evolving needs and objectives.

Now, let's take a closer look at the 10 best business analytics projects that you can undertake to delve into the intricacies of this dynamic field.

1. Market Basket Analysis

Explore the fascinating patterns in customer shopping behaviors. Understand which products are commonly purchased together and learn how to enhance recommendation systems and optimize store layouts. This project is a gateway to understanding customer preferences and contributing to a company's sales strategy.

2. Customer Review Sentiment Analysis

Gain a comprehensive understanding of customer sentiments through the analysis of product reviews. Acquire the skills to interpret customer emotions, utilizing this insight to enhance product features, resolve issues, and cultivate an outstanding customer experience. Engage in this practical project to demonstrate your capacity to establish a personal connection with customers.

3. Price Optimization

Acquire expertise in the strategic task of setting optimal prices for products. Analyze historical data, market conditions, and customer profiles to make informed decisions. This project equips you with the skills to navigate the dynamic pricing world, a crucial aspect for any aspiring business analyst entering a competitive market landscape.

4. Sales Data Analysis

Immerse yourself in the core of business success by exploring sales data. Learn how to understand customer behavior, what they purchase, and when. This analysis equips you with the skills to predict future sales trends, a valuable asset for any aspiring business analyst looking to contribute to a company's growth.

5. Customer Churn Rate Prediction

Sharpen your ability to understand and predict customer loyalty by learning how to foresee and minimize churn rates. Churn rates reveal the percentage of customers who stop using a product or service. Mastering this project allows you to proactively address concerns and enhance customer satisfaction, a vital skill for any budding business analyst.

6. Stock Market Data Analysis

Delve into the intricacies of the stock market to make well-informed investment decisions. Analyze daily price changes, trading volumes, and historical patterns to understand market behavior. This project empowers you to make strategic choices and positions you as a data-savvy business analyst who can navigate the dynamic landscape of financial markets.

7. Customer Segmentation

Hone your marketing skills by mastering the art of customer segmentation. Categorize customers based on behavior, interests, and loyalty. This practical guide enables you to direct marketing efforts effectively, save resources, and maximize profits by tailoring strategies to specific target groups. It is a foundational skill for any aspiring business analyst looking to contribute to impactful and targeted marketing campaigns.

8. Fraud Detection

Arm yourself with advanced skills in fraud detection, a critical area in the realm of business analytics. Learn to analyze intricate patterns in data to identify anomalies, from credit card fraud to cyber attacks . Mastery in fraud detection not only safeguards the financial integrity of a business but also positions you as a vigilant business analyst capable of addressing evolving challenges in the digital landscape.

9. Life Expectancy Analysis

Embark on a comprehensive exploration of the factors influencing life expectancy in a region. Analyze correlations between economic indicators, environmental conditions, political landscapes, and social trends. This project provides invaluable insights for those aspiring to contribute to public health initiatives and societal well-being, establishing you as a business analyst with a holistic understanding of the factors shaping community health.

10. Building a BI App

Familiarize yourself with Business Intelligence (BI) applications like Microsoft Power BI, going beyond surface-level understanding. This hands-on project allows you to showcase your data visualization skills fully. Building a BI app enhances your proficiency and positions you as a forward-thinking business analyst capable of transforming complex data into meaningful insights for informed decision-making in diverse organizational settings.

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In conclusion, business analytics projects open the door to a world of possibilities, allowing you to hone your analytical prowess and make a tangible impact on business strategies. Whether predicting sales trends, enhancing customer experiences, or safeguarding against fraud, these projects offer a valuable learning experience.

For those seeking to sharpen their business analytics skills further and dive deeper into strategic decision-making, consider exploring Simplilearn’s Post Graduate Program in Business Analysis . This extensive program is crafted to equip you with the necessary knowledge and tools to adeptly navigate the intricacies of strategic decision-making using proficient business analytics.

1. What qualifications are needed for a business analyst? 

Certain positions may give preference to or require a master's degree, particularly for senior roles. A bachelor's degree in business, finance, economics, information technology, or a closely related field is generally necessary. 

2. How do business analysis techniques vary across industries? 

IT and Software Development is about translating business needs into software requirements. In Finance, the focus is on financial concepts, modeling, and risk management, tailoring the approach to the sector's demands.

3. What are the common pitfalls in business analysis projects? 

Common pitfalls include insufficient stakeholder involvement, unclear requirements, communication gaps, and misalignment with business goals. Proactive communication and adaptability are key to navigating these challenges.

4. How can technology enhance business analysis?

Technology streamlines processes automates data analysis, and fosters stakeholder collaboration. Tools like data analytics software and project management platforms contribute to efficient and accurate business analysis, enabling deeper insights and informed decision-making in a data-driven landscape.

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