Top 30 Data Analytics Projects in 2024 [With Source Code]

Data analytics has become the need of the hour in almost every business organization across the globe due to advancements in technology for acquiring, storing, and analyzing vast amounts of data. Through the analysis of such information, it becomes possible to make more effective decisions in managing operations, clients, markets, and competitors. It also helps optimize the company’s performance indicators, increase the value of customers’ experiences, achieve higher revenues, minimize spending, and eliminate threats from competitors. Practicing data analytics scenarios is the best way to stay current and develop proficiency. 

If you are looking to build successful careers in data analytics, then consider pursuing a relevant online Data Science course and working on relevant data analytics projects to develop expertise in this field.

What are Data Analytics Projects?

Data analytics entails extracting knowledge from the available data through a process of calculation and evaluation using such mathematical tools as statistics and computation. With the models, they run from simple descriptive analysis to more complex modeling like the predictive model and machine learning. Such projects provide real-life exposure and a learning opportunity to its participants in the field of data analytics.

List of Data Analytics Projects

Worry not, I will be sharing some important data analytics projects that would help you grow from a Beginner in Data Analytics to an Advanced wizard! This section is divided into 3 subsections that talk about different project ideas for data analytics at each level: Beginner, Intermediate and Advanced.

Data Science Project for Beginners	Intermediate Data Analytics Projects	Advanced Data Analytics Projects
Exploratory Data Analysis of a Dataset	Social Media Sentiment Analysis	Customer Segmentation
Predictive Modeling	Fraud detection	Medical diagnosis
Interactive Data Visualization	Time Series Analysis	Human Activity Recognition (HAR)
Customer Segmentation	Customer Lifetime Value Prediction	Deep Learning for Image Recognition
Sentiment Analysis of Product Reviews	Image Classification	Time Series Anomaly Detection
Exploring COVID-19 Data	Natural Language Processing (NLP) for Text Classification	Graph Analytics
Marketing Campaign Analysis	Market Basket Analysis	Natural Language Processing (NLP) for Language Generation
Stock Market Analysis	Recommendation System with Collaborative Filtering	Predictive Maintenance
Website Traffic Analysis	Anomaly Detection	Deep Reinforcement Learning for Game Playing
Movie Recommendation System	Customer Churn Prediction	Deep Learning for Time Series Forecasting

Related: Top Data Science Project Ideas

Top Data Analytics Project Ideas for Beginners

For beginners in data analytics, it is recommended to start with smaller, more manageable data analytics projects for resume that focus on fundamental concepts and techniques. Some popular data analytics projects for beginners include analysing sales data to identify trends and patterns, exploring customer behaviour and preferences, and creating interactive dashboards to visualize data.

1. Exploratory Data Analysis of a Dataset

This project involves analysing a dataset using Python libraries such as Pandas, Matplotlib, and Seaborn to explore the data and gain insights. For example, you could analyze a dataset of Diamonds to understand how different features of the Diamond like Carat, Cut, Colour etc determine the price of the Diamond. 

The code example and the link to the dataset for this project can be found in this source code.

2. Predictive Modeling

This project involves using Python libraries such as Scikit-Learn etc. to build a predictive model from a dataset. For example, you could build a model to predict the likelihood of a person having diabetes or not based on features related to the patient’s health.

Code example and dataset for this project can be found in this source code.

3. Interactive Data Visualization

This project involves creating an interactive data visualization using Python libraries such as Plotly or Bokeh. For example, you could create a dashboard to visualize various metrics (like GDP per Capita, Life expectancy etc) of countries and their growth over a period of time. 

Code examples and datasets for this project can be found in this source code.

Data Science Bootcamp offered by upGrad, allows you to work on similar projects with each data analytics concept you master.

4. Customer Segmentation

This project entails segmentation of a company’s clientele market in order to classify the customers based on certain attributes like age, purchasing behavior, or interests. Conventional tools such as k-means clustering are used when trying to find and classify these segments so that marketing strategies can be implemented.

5. Sentiment Analysis of Product Reviews

This project creatively involves customer remarks where the comment can be classified as a positive one, a negative one or even a neutral one. Hybrid sentiment analysis is made to categorize customers’ attitude using natural language processing techniques to enhance business’s products and services.

6. Exploring COVID-19 Data

Based on COVID-19 presented data which are available to the public, this project involves tracking the virus, monitoring its areas of high prevalence or increases, and assessment of the containment measures’ efficacy. Some of the mitigation techniques used from the set include data visualization techniques, trending techniques, and model predictive analysis.

7. Marketing Campaign Analysis

This project entails assessing marketing communication activities for their ability to influence consumer responses through metrics such as click through rates and conversion rates, together with return on investment (ROI). It should be appreciated that the purpose of such comparison is to determine best practices and/or potential opportunities for growth.

8. Stock Market Analysis

This project involves using historical data of the stock markets for the purpose of recognizing trends and behaviors. Machine learning models and time analyses are employed to forecast stock prices in order to make good investment patterns.

9. Website Traffic Analysis

This project deals with website traffic analogy and its goals include identifying patterns of user behavior, degree of site popularity, and trends in various promotional campaigns. In this case, there are web analytics tools and techniques that are used in the process.

10. Movie Recommendation System

The system in this project entails making recommendations of movies to users based on their profile, particularly past movie choices. Implementing techniques such as collaborative filtering and content-based filtering, the recommendation services can be developed.

Data Analytics Projects for Intermediate

1. Social Media Sentiment Analysis

This project emphasizes in predicting the sentiment of the tweet/text based on the dataset the model is trained on. It an interesting data analytics project for final year students as one gets to explore different concepts of Natural Language Processing and Predictive Modelling. 

You can read more about the dataset and code example of one such project in this source code.

2. Fraud detection

It is one of the most critical applications of data analytics. With the rise of digital transactions, there is an increasing need for effective fraud detection systems. In this project, we will use a dataset of credit card transactions to build a fraud detection model using machine learning algorithms. We will use hyperparameter tuning techniques to improve the performance of the model and reduce false positives and false negatives. 

The code and link to the dataset for this project can be found in this source code.

3. Time Series Analysis

This project uses Python libraries such as Pandas, Matplotlib, and Prophet to analyze a dataset. For example, you could analyse stock market data to identify trends and patterns over time or analyse weather data to predict future temperatures. 

Code examples and datasets for this project can be found in this source code.

4. Customer Lifetime Value Prediction

This project is an attempt to develop a model that can forecast the customer's worth, that is the total value a customer will create in a firm over the entire customer–firm interaction period. This value is generally estimated with regression models and various machine learning algorithms to assist businesses to manage their concentrations on the highly valuable customers.

5. Image Classification

This project entails the creation of models with the primary intent being categorization of images into predetermined groups. They are applied in recognition problems of objects, animals, or scenes in images such as auto-mobile, airplanes, etc.

6. Natural Language Processing (NLP) for Text Classification

This project is centered around texts and their categorization based on common activities, for example: spam identification, categorization of topics, or identification of sentiment. To accomplish this task, NLP techniques and machine learning models are employed.

7. Market Basket Analysis

This project aims at modeling transaction data in order to evaluate the relationship between commonly bought products. Such approaches, for instance, association rule mining (for instance Apriori algorithm), are applied for product positioning and advertisements management.

8. Recommendation System using Collaborative Filtering

We are required to work on this project of developing a recommendation system about the movie by using the collaborative filtering technique, which will involve predicting the users’ preferences based on the likes of the other familiar users. This is quite common in firms that provide services either web-based, such as e-commerce or web-based streaming services.

9. Anomaly Detection

This project deals with discovering the existence of novelties, which may be defined as the outliers in the data set, such as fraud or intrusion occurrences. Some of the methods are statistical methods, Machine learning, Deep learning.

10. Customer Churn Prediction

You will simply have to determine which customers are likely to churn their product or service. Classification algorithms and types of machine learning models are applied to the analysis of the customer’s behavior and transaction history to find out who should be regarded as the potential fraudster.

Advanced Data Analytics Project Topics for Experts

1. Customer Segmentation

Customer segmentation is a popular data analytics project idea for students in final year. In this project, students analyse customer data to identify different customer segments based on various factors such as demographics, purchase behaviour, and customer preferences. The goal of customer segmentation is to better understand customer needs and tailor marketing strategies to each segment. 

The details of code and dataset for Customer Segmentation can be found in this source code.

2. Medical diagnosis