Big Data

by CACMS (Centre For Advanced Computers and Management Studies) Claim Listing

This course is an ideal package for students who want to understand the basic concepts of Business Analytics and also making them familiar with field of Analytics using R language.

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Course Details

This course is an ideal package for students who want to understand the basic concepts of Business Analytics and also making them familiar with field of Analytics using R language.

Completing this course will make learner able to construe what goes behind the processing of huge volumes of data and preparing a student for a job in Big Data analytics space. 

 

Course Outline:

  • Modules 
  • Module 01 – Introduction to Big Data 
  •  Introduction to Big Data
  •  Applicability of Big Data
  •  Introduction to Big Data technologies
  •  Introduction to Hadoop
  •  Distributed Computing Basics
  •  Evolution of Distributed Systems 
  • Module 02 – Working with Hadoop and Its Components and Concepts 
  • Analysis of Hadoop
  • HDFS and Hadoop Commands
  • Introduction to MapReduce
  • How MapReduce Works
  • Pig  
  • Hive 
  • Module 03 –Scripting with Hive & HBase 
  •  Hive Data Types and File Formats
  •  Hive Query Language  
  •  HBase Architecture Details  
  •  Working with HBase  
  • Module 04 – Programming using MapReduce for Big Data - 1 
  •  Programming Concepts in Mapreduce  
  •  HDFS programming in Java
  •  MapReduce programming in Java
  •  Executing a MapReduce program
  •  Debugging & Diagnosing Mapreduce program .
  • Module 05 – Programming using MapReduce for Big Data - 2 
  •  Job Chaining & Merging
  •  Input & Output patterns
  • NextGen MapReduce using YARN & REST 
  • Module 06 – Distributed Resource synchronization using ZooKeeper 
  •  ZooKeeper in detail  
  • Module 07 – Data loading using Sqoop 
  • Sqoop in detail
  • Introduction to ETL and CDC
  • TelenD
  • o Introduction
  • o Components
  • o ETL Perspective o Installation
  • o Basic Operations
  • Module 08 – Handling large log files using Flume 
  •  Flume in detail
  •  Kafka o Introduction
  • o Architecture and workflow
  • o Installation
  • o Basic operations 
  • Module 09 – Handling workflows using Oozie 
  •  Workflow scheduling using Oozie  
  • Module 10 – Understanding Popular Big Data Platforms 
  • Cloudera, Hortonworks, Greenplum, Vertica 
  • Amritsar Branch

    SCO 9 Burj Punjab, B - Block, Amritsar

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