HomeBlogData ScienceTop 30 Data Analytics Projects in 2024 [With Source Code]

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

01st Jul, 2024
view count loader
Read it in
10 Mins
In this article
    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 ProjectsAdvanced Data Analytics Projects
    Exploratory Data Analysis of a DatasetSocial Media Sentiment AnalysisCustomer Segmentation
    Predictive ModelingFraud detectionMedical diagnosis
    Interactive Data VisualizationTime Series AnalysisHuman Activity Recognition (HAR)
    Customer SegmentationCustomer Lifetime Value PredictionDeep Learning for Image Recognition
    Sentiment Analysis of Product ReviewsImage ClassificationTime Series Anomaly Detection
    Exploring COVID-19 DataNatural Language Processing (NLP) for Text ClassificationGraph Analytics
    Marketing Campaign AnalysisMarket Basket AnalysisNatural Language Processing (NLP) for Language Generation
    Stock Market AnalysisRecommendation System with Collaborative FilteringPredictive Maintenance
    Website Traffic AnalysisAnomaly DetectionDeep Reinforcement Learning for Game Playing
    Movie Recommendation SystemCustomer Churn PredictionDeep Learning for Time Series Forecasting

    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
    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 Analyst Bootcamp offered by KnowledgeHut 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
    Medical diagnosis

    Medical diagnosis is a fascinating data analytics project idea for final year students. In this project, students use machine learning algorithms to analyse medical data and help diagnose diseases or conditions. This project can involve various types of data, including patient records, medical images, and clinical notes. To complete this project, students must have a strong understanding of machine learning algorithms and statistical analysis techniques. They must also have experience working with medical data and be familiar with programming languages such as Python or R. 

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

    3. Human Activity Recognition (HAR) 

    HRA is a compelling data analytics project idea for final year students. In this project, students use machine learning algorithms to analyse sensor data and recognize different human activities. HAR has applications in various industries, including healthcare, sports, and entertainment. To complete this project, students must have a strong understanding of machine learning algorithms and data pre-processing techniques. They must also have experience working with sensor data and be familiar with programming languages such as Python or R. 

    The code to implement this project can be found from in this source code.

    4. Deep Learning for Image Recognition

    This project encompasses the application of deep learning models whereby convolutional neural networks, commonly abbreviated as CNNs will be trained to high-recognition accuracies in image-recognition tasks including; object detection, face recognition and medical image analysis among others.

    5. Time Series Anomaly Detection

    Time series data is the focus of this project which includes identifying specialized patterns in the data set like transaction records, sensors, and network traffic. Other sophisticated methodologies are recurrent neural network (RNN), and long short-term memory (LSTM) network.

    6. Graph Analytics

    The aim of this project is to comprehend graph data of various types, for example graphs that represent a social or biological network, and to detect features including members of a community, important nodes, or shortest connections. Other methods are graphical and network analysis procedures.

    7. Natural Language Processing (NLP) for Language Generation

    This project is specifically centered around generating human-like text where conventional methods of writing or computer programs are replaced by more profound NLP techniques and models such as transformers (for example, GPT-3). Such as Chatbots, Content Generation: and Machine Translation.

    8. Predictive Maintenance

    This project entails the use of the smart maintenance system to predict the time a particular equipment will develop a fault, or the time it will need to be serviced based on records of the sensors and service history of machines in the equipment. Some of the methods include machine learning, deep learning, and data analytics based on IoT.

    9. Deep Reinforcement Learning for Game Playing

    This project entails developing unconventional reinforcement learning algorithm that can teach agents to engage and perform well in games like Go, chess, and or video games as a result of experimenting with a model or strategy.

    10. Deep Learning for Time Series Forecasting

    This project is centered on employing RNNs and LSTMs for predetermining future values on period data like stock prices, climate, or demand assessment.

    Why Should You Work on Data Analytics-Based Projects?

    Working on data analytics-based projects can have many benefits, including:

    • Developing practical skills in data analytics and machine learning
    • Enhancing your resume and making yourself more marketable to potential employers
    • Gaining real-world experience working with large datasets and complex problems
    • Making meaningful contributions to various industries, including healthcare, finance, and e-commerce
    • Having the opportunity to work on projects that can have a significant impact on society.
    • Predictive Maintenance for Industrial Machinery: Develop a machine learning model to predict equipment failures based on sensor data collected from industrial machines. This can help prevent downtime and maintenance costs.
    • Traffic Forecasting Model: Develop a time series forecasting model that can predict traffic congestion levels on highways based on historical data such as weather conditions, accident reports, roadwork updates, etc. This could help drivers plan their routes better.
    • Personalized Recommendation Engine: Create a recommendation engine that uses collaborative filtering, content-based filtering, and matrix factorization to generate personalized recommendations for users based on their past behavior, preferences, and other factors.
    • Image Classification with Convolutional Neural Networks: Implement a convolutional neural network (CNN) to classify images into different categories, such as cats vs dogs, cars vs trucks, etc.
    • Energy Saving Optimization for Building Management Systems: Develop a building management system that optimizes energy consumption by analyzing occupancy sensors, temperature readings, light levels, etc., to determine optimal settings for heating/cooling systems, lights, etc.
    • Anomaly Detection Algorithm: Create an algorithm that can identify outliers or deviations from normal patterns in datasets.
    • Sports Analytics Platform: Use statistical models to analyze player performance metrics such as batting averages, home run rates, fielding percentages, etc. This platform could provide insights to coaches and managers to make informed decisions related to draft picks, roster moves, training regiments, etc.

    Best Platforms to Work on Data Analytics Projects

    There are many platforms available for working on data analytics practice projects, ranging from free open-source tools to enterprise-level software. Some of the best platforms to work on data analytics real time projects include:

    1. Jupyter Notebook: a popular open-source web application for creating and sharing code and data visualizations
    2. Tableau: a data visualization and business intelligence tool used to create interactive dashboards and reports
    3. Python: a versatile programming language with powerful libraries for data manipulation, analysis, and visualization such as Pandas, NumPy, and Matplotlib.
    4. R: a programming language and environment for statistical computing and graphics, often used for data analysis and visualization.
    5. Apache Hadoop: an open-source framework for distributed storage and processing of large datasets
    6. Microsoft Power BI: a business analytics service that provides interactive visualizations and business intelligence capabilities
    7. KNIME Analytics Platform: a free and open-source data analytics tool for creating data pipelines and machine learning models.

    Overall, the best platform for data analytics projects for portfolio depends on the project's specific requirements, complexity, and available resources.

    Learn Data Analytics the Smart Way!

    Hold up! If all this sounds a bit overwhelming to you as a beginner in data analytics projects, then worry not! I have a solution for that too. As a beginner, you can walk towards mastering Data Analytics by enrolling on an Online Data Science Course. There are different professional prospects after getting versed in Data Science like Data Analyst and Data Scientist. To become a master data analyst, you can join the Data Analyst Bootcamp and to excel as a data scientist join the cohort of KnowledgeHut online Data Science Course!

    Hurry up! And get started.

    Frequently Asked Questions (FAQs)

    1What are the 6 types of data analytics?

    The six types of data analytics are descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics, cognitive analytics, and big data analytics. 

    2How do I get projects on data analytics?

    To get projects on data analytics, one can look for open data sources, participate in data analytics competitions, or collaborate with organizations to solve data-related problems. 

    3What are data analytics projects?

    Data analytics projects involve using big data techniques and tools to extract meaningful insights and knowledge from data. 

    4Which project is best for data analyst?

    The best project for a data analyst depends on their interests and expertise, as well as the needs of their organization or industry. 


    Ashish Gulati

    Data Science Expert

    Ashish is a techology consultant with 13+ years of experience and specializes in Data Science, the Python ecosystem and Django, DevOps and automation. He specializes in the design and delivery of key, impactful programs.

    Share This Article
    Ready to Master the Skills that Drive Your Career?

    Avail your free 1:1 mentorship session.

    Your Message (Optional)

    Upcoming Data Science Batches & Dates

    NameDateFeeKnow more
    Course advisor icon
    Course Advisor
    Whatsapp/Chat icon