Big Data Analytics

TLM – 5 Units

Syllabus Overview

Course: Big Data Analytics (BDA) – 5 Units covering fundamentals, Hadoop ecosystem, Spark, NoSQL, and analytics.

Unit 1

Introduction to Big Data

  • What is Big Data
  • Types of Big Data (Structured, Semi-structured, Unstructured)
  • 5 Vs of Big Data
  • Advantages of Big Data Analytics
  • Applications of Big Data
Theory Case Studies Activity
Unit 2

Hadoop Ecosystem

  • What is Hadoop
  • HDFS (Hadoop Distributed File System)
  • MapReduce Programming Model
  • YARN (Yet Another Resource Negotiator)
  • Hadoop Ecosystem Tools
Theory Case Studies Activity
Unit 3

Data Processing with Spark

  • Introduction to Apache Spark
  • RDDs, DataFrames, and Spark SQL
  • Spark Streaming
  • MLlib (Machine Learning Library)
  • Spark vs MapReduce
Theory Case Studies Activity
Unit 4

NoSQL Databases

  • What is NoSQL
  • Types: Document, Key-Value, Column-Family, Graph
  • MongoDB, Cassandra, HBase
  • CAP Theorem
  • SQL vs NoSQL
Theory Case Studies Activity
Unit 5

Big Data Analytics & Visualization

  • Types of Analytics (Descriptive, Diagnostic, Predictive, Prescriptive)
  • Data Mining Techniques
  • Machine Learning for Big Data
  • Data Visualization Tools
  • Real-world Applications
Theory Case Studies Activity

Resources

Lab Manual

9 hands-on experiments covering all 5 units

Open Lab Manual

Glossary & Formulas

40+ terms and 15+ key formulas

Open Annexure

Textbook References

1. Tom White, "Hadoop: The Definitive Guide"

2. Jeffrey Nunn, "Learning Spark"