Big Data in Real Life: Projects & Case Studies

Categories: BIG DATA

About Course

Big Data in Real Life: Projects & Case Studies is a hands-on course designed to bridge the gap between theory and practice. You’ll work with real-world datasets and analyze actual industry case studies to understand how Big Data transforms operations, marketing, risk management, healthcare, logistics, and beyond.

Ideal for data enthusiasts, aspiring professionals, and project-based learners, this course focuses on solving real business challenges using data pipelines, visualizations, and data-driven decision-making strategies. Each module includes practical projects and domain-specific applications using popular tools like Hive, Spark, SQL, and Python.

How Big Data is applied in industries like finance, retail, healthcare, and logistics
End-to-end workflows from data ingestion to visualization
Use of Hive, Spark, Python, and SQL in real-world scenarios
How to interpret dashboards and KPIs from Big Data projects
Storytelling with data through case documentation and reports
Structuring Big Data projects for career portfolios

Course Content

Module 1: Introduction to Real-World Big Data
Understanding industry demand for Big Data Overview of end-to-end data pipeline

Module 2: Case Study – E-Commerce Customer Insights
Data cleansing and profiling Behavioral segmentation using Spark & SQL Building dashboards for customer analytics

Module 3: Case Study – Healthcare Predictive Analytics
Patient data anonymization and integration Predicting hospital readmission rates Use of machine learning models (optional overview)

Module 4: Case Study – Fraud Detection in Finance
Transaction pattern recognition Rules-based filtering and anomaly detection Real-time data streaming use cases

Module 5: Hands-on Mini Projects
Project 1: Retail sales trend analysis using Hive Project 2: Public dataset project (COVID-19, stock, sports, etc.) Project 3: Build a data pipeline from scratch

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Big Data in Real Life: Projects & Case Studies

About Course

What Will You Learn?

Course Content

Module 1: Introduction to Real-World Big Data
Understanding industry demand for Big Data Overview of end-to-end data pipeline

Module 2: Case Study – E-Commerce Customer Insights
Data cleansing and profiling Behavioral segmentation using Spark & SQL Building dashboards for customer analytics

Module 3: Case Study – Healthcare Predictive Analytics
Patient data anonymization and integration Predicting hospital readmission rates Use of machine learning models (optional overview)

Module 4: Case Study – Fraud Detection in Finance
Transaction pattern recognition Rules-based filtering and anomaly detection Real-time data streaming use cases

Module 5: Hands-on Mini Projects
Project 1: Retail sales trend analysis using Hive Project 2: Public dataset project (COVID-19, stock, sports, etc.) Project 3: Build a data pipeline from scratch

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About Course

What Will You Learn?

Course Content

Module 1: Introduction to Real-World Big Data Understanding industry demand for Big Data Overview of end-to-end data pipeline

Module 2: Case Study – E-Commerce Customer Insights Data cleansing and profiling Behavioral segmentation using Spark & SQL Building dashboards for customer analytics

Module 3: Case Study – Healthcare Predictive Analytics Patient data anonymization and integration Predicting hospital readmission rates Use of machine learning models (optional overview)

Module 4: Case Study – Fraud Detection in Finance Transaction pattern recognition Rules-based filtering and anomaly detection Real-time data streaming use cases

Module 5: Hands-on Mini Projects Project 1: Retail sales trend analysis using Hive Project 2: Public dataset project (COVID-19, stock, sports, etc.) Project 3: Build a data pipeline from scratch

Student Ratings & Reviews

Trending Courses

Trending College Workshops

Company

Contact

Categories

Module 1: Introduction to Real-World Big Data
Understanding industry demand for Big Data Overview of end-to-end data pipeline

Module 2: Case Study – E-Commerce Customer Insights
Data cleansing and profiling Behavioral segmentation using Spark & SQL Building dashboards for customer analytics

Module 3: Case Study – Healthcare Predictive Analytics
Patient data anonymization and integration Predicting hospital readmission rates Use of machine learning models (optional overview)

Module 4: Case Study – Fraud Detection in Finance
Transaction pattern recognition Rules-based filtering and anomaly detection Real-time data streaming use cases

Module 5: Hands-on Mini Projects
Project 1: Retail sales trend analysis using Hive Project 2: Public dataset project (COVID-19, stock, sports, etc.) Project 3: Build a data pipeline from scratch