Big Data Analytics

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BIG DATA ANALYTICS ME02095021
FREE PDF ME02095021
Code: ME02095021 Credits: 4 Semester 2 AIAD

Big Data Analytics

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Big Data Analytics Syllabus — Unit-wise Content

The official GTU curriculum for Big Data Analytics (subject code ME02095021) as prescribed for AIAD · Semester 2 divides the course into 6 units, covering 38 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (ME02095021)

Unit 1 Unit-I

5 lecture hours

  • Introduction to Big Data and Hadoop Introduction– distributed file system–Big Data and its importance
  • Four Vs, Drivers for Big data
  • Big data analytics
  • Big data applications
  • Algorithms using map reduce
  • Big Data – Apache Hadoop & Hadoop Eco System
  • Moving Data in and out of Hadoop – Understanding inputs and outputs of MapReduce –Data Serialization

Unit 2 Unit-II

9 lecture hours

  • HIVE AND HIVEQL
  • HBASE HDFS-Overview
  • Installation and Shell
  • Java API
  • Hive Architecture and Installation
  • Comparison with Traditional Database
  • HiveQL Querying Data
  • Sorting And Aggregating
  • Joins & Sub queries
  • HBase concepts
  • Advanced Usage
  • Schema Design
  • Advance Indexing, PIG, Zookeeper
  • how it helps in monitoring a cluster

Unit 3 Unit-III

7 lecture hours

  • Data Analysis with Spark Shell Writing Spark Application - Spark Programming in Scala
  • Python, R, Java - Application Execution

Unit 4 Unit-IV

8 lecture hours

  • NoSQL What is it?Where It is Used Types of NoSQL databases
  • Why NoSQL? Advantages of NoSQL
  • Use of NoSQL in Industry
  • SQL vs NoSQL
  • Database for the Modern Web Program Name: Master of Engineering Level: PG Branch: Artificial Intelligence and Data Science Subject Code: ME02095021 Course/Subject Name: Big Data Analytics

Unit 5 Unit-V

10 lecture hours

  • Spark SQL and GraphX Introduction to MongoDB key features
  • Core Server tools
  • MongoDB through the JavaScript’s Shell
  • Creating and Querying through Indexes
  • principles of schema design
  • Constructing queries on Databases
  • collections and Documents
  • MongoDB Query Language
  • SQL Context – Importing and Saving data – Data frames – using SQL – GraphX overview – Creating Graph – Graph Algorithms

Unit 6 Unit-VI

6 lecture hours

  • Current Trends The latest technology and algorithms in data analytics for real time applications

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