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Big Data & Hadoop Training in Jaipur

  • Big Data & Hadoop

    Hadoop Development course teaches the skill set required for the learners how to setup Hadoop Cluster, how to store Big Data using Hadoop (HDFS) and how to process/analyze the Big Data using Map-Reduce Programming or by using other Hadoop ecosystem. Attend the Hadoop Training demo by Real-Time Expert.

    Hadoop is an Apache open-source framework written in Java that allows distributed processing of large data sets across clusters of computers using simple programming models. A Hadoop frame-worked application works in an environment that provides distributed storage and computation across clusters of computers. Hadoop is designed to scale up from a single server to thousands of machines, each offering local computation and storage.

  • LEARNING OUTCOMES

    • Gain in-depth knowledge of Big Data and Hadoop & its ecosystem
    • Master real-time data processing using various tools
    • Become expert in working on data, and managing data resources
    • Become a functional programmer implementing various applications to ensure effective data processing and optimization techniques are in place
    • Expert knowledge to apply interactive algorithms and work on data forms
    • Exhibit capability to ingest and analyze large data-sets
    • Recommend solutions based on analysis done

Azure 300 Training & Certification Course Content

  • Basics of Big data
  • Big Data Generation
  • Big Data Introduction
  • Big Data Architecture
  • Understand Big data Problem
  • Big data Management Approach
  • Traditional and Current Data storing approach
  • Understand various data formats and data units
  • Big data With Industry Requirements
  • Big Data Challenges
  • Understand Hadoop Environment
  • Requirement of Hadoop
  • Importance of Data Analytics
  • Setting up Hadoop Environment
  • Hadoop advantages over RDBMS
  • Explaining Various file systems
  • Hdfs GFS, POSIX, GPFS
  • Explain clustering methodology
  • Master Nodes and slave nodes
  • Working on his File System
  • Creating lib and accessing lib from HDFS
  • Hadoop commands mkdir, delete dir, etc
  • Working with a web console
  • Introduction of Map Reduce
  • MapReduce programming and word count
  • MapReduce nodes job tracker and task tracker
  • Running MapReduce program through the web console
  • Introduction of JAQL Approach
  • Understand the information stream
  • Understand Information ocean
  • Working with JAQL Language
  • Understand Data WareHousing
  • The requirement of Data Warehousing
  • Data Warehousing with Hive
  • Understand the Hive environment
  • Working with Hive Query Language
  • Perform DDL approach Through Hive
  • Perform a DML approach through Hive
  • Introduction of PIG
  • Requirement of Pig
  • Working with pig Script
  • Running and managing Pig Script
  • Perform Streaming Data Analytics through PIG
  • Pig Advantages and Disadvantages
  • Understand Flume methodology
  • Requirement of flume
  • flume advantages
  • working lab with flume
  • introduction of Sqoop
  • Requirement of Sqoop
  • advantages of Sqoop