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Workshop Goals Benefits for Participants
  • Understand the basics of Big data
  • Learn to Google Map/Reduce, Map/Reduce Programming
  • Learn to Hadoop Programming
  • Learn to manage Big Data by using Hadoop
  • Learn to advancement in Hadoop for enhancing performance of operations
  • Learn to implement Hadoop File system (HDFS)
  • Learn to Case studies over Hadoop technology
  • Learn to use Spark & Zeppelin for Data Analytics
  • Grasp all the knobs & levers for running Hadoop
  • Use Hadoop for a variety of data analysis tasks
  • Understand the challenges of Hadoop & its future
  • How Hadoop is useful in their academics or projects
  • Best for those who want to be a Data Scientist
  • Best applied in most of Companies
  • Participants get basic knowledge of it earlier so it make good impact on career
  • Certificates to every participant from organization


  • Workshop Prerequisites
  • Students should have basic knowledge of Java
  • Auditorium or Lab with projector & mike system
  • Lab with Ubuntu 14.04 32 bit Min. 4 GB RAM
  • Student should carry their own laptops with above configuration
  • Coordinator team (2 Technical assistant)
  • One Board with Marker
  • Student should arrange in single Lab so that we can co-ordinate well.


  • Workshop Agenda

    Time Subject Content
  • Day 1:

  • 9:30Hrs to 01:30Hrs
  • Big Data & Hadoop
  • Introduction to Data Analytics
  • Introduction to Big Data
  • What is Big Data
  • Problems with Big Data
  • Idea Behind Hadoop
  • Structured VS Unstructured Data
  • Big Data & Hadoop Strategy
  • Introduction to Hadoop
  • Need of Hadoop
  • History behind Hadoop
  • Name Evolution
  • Hadoop Usage
  • Hadoop Limitations
  • Future of Hadoop
  • Map/Reduce
  • What is Data Analytics
  • 02:00Hrs to 05:00Hrs
  • Google Map/Reduce
  • WordCount Program
  • What is Google Map/Reduce
  • Google Map/Reduce structure
  • Relation between Hadoop & Map/Reduce
  • Hadoop Map/Reduce programming
  • Hadoop Setup
  • Installation of Hadoop
  • WordCount Program Handson
  • 05:00 Hrs to 05:30 Hrs QA Session QA Session
  • Day 2:

  • 9:30Hrs to 01:30Hrs
    Visualization Techniques for Analytics
  • Introduction to Real Time Analytics
  • Real time projects of Analytics
  • Installation of Zeppelin
  • Python NoteBook
  • Zeppelin Tool Demo
  • 02:00Hrs to 05:00Hrs
  • Hands on with Zeppelin
  • QA Session
  • One Mini Project with Zeppelin Tool
  • Recent Trends in Bigdata & Career Opportunity in it
  • Research Trends in IT
  • QA Session & Career Opportunity with Hadoop & Bigdata
  • Day 3:

  • 9:30Hrs to 10:30Hrs
    Introduction to YARN
  • How is it different
  • MapReduce-2
  • 10:30Hrs to 12:30Hrs
  • Introduction to NOSQL
  • Apache Hive
  • Introduction to Apache Hive
  • Installation of Hive
  • Work with Hive
  • 12:30Hrs to 1:30Hrs
  • Introduction to SQOOP
  • SQOOP Installation
  • Installation of Sqoop
  • Working with Sqoop
  • 2:00Hrs to 5:00Hrs Introduction to MongoDB
  • Installation of MongoDB
  • Working with MongoDB
  • MongoDB Assignments
  • Hands on Assignments
  • 5:00Hrs to 5:30Hrs QA Session QA Session