Big Data with Hadoop


Big Data needs no introduction in today’s world! In fact, it is becoming a crucial way for leading companies to outperform their competitors. All the companies are taking strategic initiatives to leverage the big data revolution to innovate, compete, and capture value. Those who possess the skills in these domains making inroads into the future.

Why to take this course?

Big Data is fastest growing and most promising technology for handling large volumes of data for doing data analytics. This comprehensive Big Data Hadoop training will help you to elevate your career into the most demanding field. Forbes quoted “big Data Analytics & Hadoop Market accounted for $8.48B in 2015 and is expected to reach $99.31B by 2022 growing at a CAGR of 42.1% from 2015 to 2022“. 

Who can benefit from this course ?

  • Programming Developers and System Administrators
  • Business Intelligence, Data warehousing and Analytics Professionals
  • Graduates, undergraduates eager to learn the latest Big Data technology

    Course Outline

    Introduction to Big Data 
    • Big Data Vs traditional data
    • Business importance of Big Data
    • The four dimensions of Big Data: volume, velocity, variety, veracity
    • Introducing to Storage, MapReduce and Query Stack
  • Installation – Hadoop
    • Introduction/ Refreshment of Ubuntu and RHEL
    • Establishment of JAVA Developer.
    • Practical Establishment of Virtual Environment (OVM).
    • Installation of Ubuntu 16 Desktop
    • Installation of Hadoop 2x
    • Introduction to HDFS.
    • Handling XML & Scripts On Hadoop administrator
Installation and Establishment of Ecosystems
  • PIG, HIVEQL, MYSQL, SPARK, SQOOP, Flume, Hbase and Zookeeper
Processing and Data Analyzing Big Data

Mapping data to the programming framework and extracting data from storage
Tools and Techniques to Analyze Big Data.
Data handling on MYSQL
Establish MySQL and Ecosystem relateion as Connecter setting
Executing and Monitoring Hadoop MapReduce jobs
Hadoop Map-Reduce using PIG
Hadoop Map-Reduce using HiveQL.
Loading data using – SQOOP and Flume
Executing commands using the Grunt Shell
Handling streaming data
Creating business value from extracted data
Selecting appropriate execution modes: local, pseudo-distributed and fully distributed

Developing a Big Data Strategy
  • Establishment method using HBASE.
  • Establishment method using SPARK.
  • Establishment method using JAVA
  • Introduction to Horton Works and Cloudera
Introduction to R with Hadoop
  • Enlightenment of Jaspersoft (reporting and analytics server), Pentaho (data integration and business analytics), Splunk (platform for IT analytics), Talend (big data integration, data management and application integration)
    Delivery Model
  • The Workshop consists of class lectures by experts in Big Data analytics, demos, individual & group lab exercises and case studies