This repository contains my academic submission for the Big Data Analytics (BDA601) course. The assignment focuses on the transition from traditional Business Intelligence (BI) systems to modern Big Data platforms, along with their architecture, analytics, and real-world applications.
The project explores how organizations manage large-scale data and use Big Data technologies for faster, real-time decision-making compared to traditional BI systems.
A Netflix-based case study explaining data collection, personalization, real-time recommendations, and the 5Vs of Big Data (see infographic in the report, page 3).
A role-play discussion highlighting the limitations of traditional BI and the importance of real-time analytics, scalability, Hadoop, and NoSQL.
Comparison of traditional data warehouse and modern Big Data architecture, including Hadoop, Spark, streaming, and distributed processing (pages 6–7).
Mapping business problems to analytics types:
- Descriptive
- Diagnostic
- Predictive
- Prescriptive
Hadoop, Spark, HDFS, NoSQL, Streaming, BI Tools (Power BI, Tableau), Machine Learning fundamentals.
- Understanding of Big Data concepts and architecture
- Exposure to modern analytics approaches
- Awareness of real-world business applications
Jhashank Nayan Computer Science & Engineering (Data Science) Acharya Institute of Technology
📄 Refer to the submitted report in this repository for full details.