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Big Data Analytics on Hadoop

BigData Analytics on Hadoop _ Level 2

Duration: 2 Days


This course is recommended as an advancement to Processing BigData on Hadoop. While Processing BigData was geared more towards devlopers who wanted to understand how to use Hadoop to handle and arrange BigData, this course will go on to teach how to perform analytical operations to gain insights from data processed through Hadoop. BigData Analytics on Hadoop will teach you all you need to learn about BigData Analytics on Hadoop.

Big Data is a popular term used to describe the exponential growth, availability and use of information, both structured and unstructured. It is imperative that organizations and IT leaders focus on the ever-increasing volume, variety and velocity of information that forms BigData. Hadoop is the core platform for structuring BigData, and solves the problem of making it useful for Analytics.

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  • The basics of Hadoop , Mapreduce, Pig Latin (the coding language)
  • The basics of Analytics – Concepts , Data preparation – merging, managing missing numbers sampling , Data visualisation, Basic statistics
  • Lots of practise to ensure that we are very comfortable handling an Analytics project on BigData

Who Should Attend

  • Data analysts / Data scientists who want to know how to use their expertise on Big Data
  • Database Managers with a knowledge of Hadoop / Java who want to know what to do next in their career and how to manage and draw insights from their data
  • Consultants who want to know what Big Data analytics is



  • A though understanding about Big Data and Hadoop

Course Outline

Day 1

  • What is Big Data? What is Hadoop?
  • Anatomy of HDFS; blocks of data ;
  • How to extract data from Hadoop- basic understanding of how to write code
  • Map reduce – a programmer’s tool – brief introduction
  • Pig Latin – Reading data – data retrieval ; saving datasets
  • Data Preparation and Management
    • Types of variables
    • Identifying the business Y
    • Basic Statistics
    • Merging and Appending data – Primary key concept
    • Missing values
    • Outliers


Day 2

    • Data visualisation-Graphs , Charts – the basics
    • Normal Distribution
    • Correlation , Covariance
    • Sampling
    • Hypothesis Testing
      • T Test
      • Annova
  • Deductive Vs  Inductive reasoning
  • Process of Analysis

About The Trainer


Subhashini S Tripathi
Trainer , Blogger and Consultant – Analytics and E-Learning

Subhashini S TripathiSubhashini has 11+ years of work experience in Retail Banking Analytics and in Training and Consulting for Analytics. She has worked in roles in the area of Risk Management (pre-acquisition, post-acquisition and portfolio management), Collections strategy, Fraud Control and Marketing Analytics with GE Money, Standard Chartered Bank, Tata Motors Finance and Citi GDM .

From Jan 2012 onward, she is active in the Analytics Training, Blogging and Consulting arena.Her area of interest is amalgamating numbers with business strategy and decision making.

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Other Details


For latest batch dates, fees, location, technical queries and general inquiries, contact our sales team at: +91 8880002200 or email at

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