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Big Data analytics Training

Big Data analytics with Hadoop & R


  1. Deploying the Data Analytics Lifecycle to address big data analytics projects
  2. Reframing a business challenge as an analytics challenge
  3. Applying appropriate analytic techniques and tools to analyze big data, create statistical models, and identify insights that can lead to actionable results
  4. Selecting appropriate data visualizations to clearly communicate analytic insights to business sponsors and analytic audiences
  5. Using tools such as: R, Map Reduce/Hadoop, in-database analytics

Big Data Analytics Training


Programming experience and exposure with Data related work such as Reporting, Data Integration, Database Management etc.


What is Big Data & Why Hadoop?

  • Big Data Characteristics, Challenges with traditional system

Hadoop Overview &it’s Ecosystem

  • Anatomy of Hadoop Cluster, Installing and Configuring Hadoop

  • Hands-On Exercise

HDFS – Hadoop Distributed File System

  • Name Nodes and Data Nodes

  • Hands-On Exercise

Map Reduce Anatomy

  • How Map Reduce Works?

  • The Mapper & Reducer, Input Formats & Output Formats, Data Type & Customer Writable

Developing MapReduce Program

  • Setting up Eclipse Development Environment, Creating Map Reduce Projects,Debugging and Unit Testing MapReduce Code, Testing with MRUnit

Hive, pig & Mahout

  • Hands-On Exercise

 R and Hadoop Overview

  • Introduction to R tool

  • R and Hadoop Integration

  • Hadoop Streaming using R

  • RHadoop Overview

  • RHive Overview

Analytics Project Methodology

  • Analytics Project Overview

  • Steps Invovled in Aanlytics Project

  • Analytics Techniques and Applications in Business

  • Implications of Big Data on Analytics

Working with RHadoop & RHive

  • Word Count Example

  • Airline Optimization Example

  • Retail Store Example

  • Stocks Example

Business Case Study

  • Big Data Analytics Case Study

  • Problem Identification and Solution Design

  • Data Analysis and Visualization

  • Final Insights and Recommendations


Who should learn Big Data Analytics?

This course is intended for individuals seeking to develop an understanding of Data Science from the perspective of a practicing Data Scientist, including:

  1. Managers of teams of business intelligence, analytics, and big data professionals
  2. Current Business and Data Analysts looking to add big data analytics to their skills.
  3. Data and database professionals looking to exploit their analytic skills in a big data environment.
  4. Recent college graduates and graduate students with academic experience in a related discipline looking to move into the world of Data Science and big data.

Big Data Training Bangalore Hadoop Training in Bangalore, 2013