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Big Data Course Objectives

  • To form a concrete understanding of the basics of Data Analysis
  • Understanding about computational tools at application level
  • Enable the trainees to handle Data / Statistical analysis better
  • Introduction Data: its types, ways of analyzing, types of systems
  • Best possible knowledge in Big Data, its requirements and challenges
  • Know what id a Hadoop, its installation, configuration and different modes
  • Create an Ubuntu image in VMware
  • Hadoop Distribution of File System
  • Understanding block and input splits, Map Reduce Programming, and its function
  • Detail oriented classes in advanced concepts like PIG, Sqoop, HBase and Yarn

Big Data Hadoop Course Syllabus

  • 1: Hadoop Introduction

  • Introduction to Data and System
  • Types of Data
  • Traditional way of dealing large data and its problems
  • Types of Systems & Scaling
  • What is Big Data
  • Challenges in Big Data
  • Challenges in Traditional Application
  • New Requirements
  • What is Hadoop? Why Hadoop?
  • Brief history of Hadoop
  • Features of Hadoop
  • Hadoop and RDBMS
  • Hadoop Ecosystem’s overview

  • 2: Hadoop Installation

  • Installation in detail
  • Creating Ubuntu image in VMware
  • Downloading Hadoop
  • Installing SSH
  • Configuring Hadoop, HDFS & MapReduce
  • Download, Installation & Configuration Hive
  • Download, Installation & Configuration Pig
  • Download, Installation & Configuration Sqoop
  • Download, Installation & Configuration Hive
  • Configuring Hadoop in Different Modes

  • 3: Hadoop Distribute File System (HDFS)

  • File System - Concepts
  • Blocks
  • Replication Factor
  • Version File
  • Safe mode
  • Namespace IDs
  • Purpose of Name Node
  • Purpose of Data Node
  • Purpose of Secondary Name Node
  • Purpose of Job Tracker
  • Purpose of Task Tracker
  • HDFS Shell Commands – copy, delete, create directories etc.
  • Reading and Writing in HDFS
  • Difference of Unix Commands and HDFS commands
  • Hadoop Admin Commands
  • Hands on exercise with Unix and HDFS commands
  • Read / Write in HDFS – Internal Process between Client, NameNode & DataNodes
  • Accessing HDFS using Java API
  • Various Ways of Accessing HDFS
  • Understanding HDFS Java classes and methods
  • Commissioning / DeCommissioning DataNode
  • Balancer
  • Replication Policy
  • Network Distance / Topology Script

  • 4: Map Reduce Programming

  • About MapReduce
  • Understanding block and input splits
  • MapReduce Data types
  • Understanding Writable
  • Data Flow in MapReduce Application
  • Understanding MapReduce problem on datasets
  • MapReduce and Functional Programming
  • Writing MapReduce Application
  • Understanding Mapper function
  • Understanding Reducer Function
  • Understanding Driver
  • Usage of Combiner
  • Usage of Distributed Cache
  • Passing the parameters to mapper and reducer
  • Analysing the Results
  • Log files
  • Input Formats and Output Formats
  • Counters, Skipping Bad and unwanted Records
  • Writing Join’s in MapReduce with 2 Input files. Join Types
  • Execute MapReduce Job - Insights
  • Exercise’s on MapReduce

  • 5: Hive

  • Hive concepts
  • Hive architecture
  • Install and configure hive on cluster
  • Different type of tables in hive
  • Hive library functions
  • Buckets
  • Partitions
  • Joins in hive
  • Inner joins
  • Outer Joins
  • Hive UDF
  • Hive Query Language

  • 6: PIG

  • Pig basics
  • Install and configure PIG on a cluster
  • PIG Library functions
  • Pig Vs Hive
  • Write sample Pig Latin scripts
  • Modes of running PIG
  • Running in Grunt shell
  • Running as Java program
  • PIG UDFs

  • 7: Sqoop

  • Install and configure Sqoop on cluster
  • Connecting to RDBMS
  • Installing Mysql
  • Import data from Mysql to hive
  • Export data to Mysql
  • Internal mechanism of import/export

  • 8: HBase

  • HBase concepts
  • HBase architecture
  • Region server architecture
  • File storage architecture
  • HBase basics
  • Column access
  • Scans
  • HBase use cases
  • Install and configure HBase on a multi node cluster
  • Create database, Develop and run sample applications
  • Access data stored in HBase using Java API
  • Map Reduce client to access the HBase data

  • 9: YARN

  • Resource Manager (RM)
  • Node Manager (NM)
  • Application Master (AM)
Download Full Big Data Hadoop Training Course Syllabus Now

Students Feedback for Big Data Training in Chennai

Jainsy Anjirwala

I thank Apponix for offering the best online training experience. It was very informative. The training helped a lot in my career.

Big Data Expert
Jaya Jayasree

The classes are too good. The trainer did his best in explaining the topics. The subject is made clear through enough examples and methods. Thanks a lot sir.

Big Data Analyst
Kajal Thakkar

Excellent learning experience. I recommend others too to join Apponix to have the best online technical trainings. Well organized classes.

Big Data Analyst
subrat Mr. Srikanth

8+ years of working experience in MNC

Big Data Hadoop Trainer Profile

  • Having 8 years of experience in advanced language features in Big Data Hadoop
  • Trained more than 1000+ students on Big Data Hadoop.
  • 5 * rating from all our students.
  • Having good experience developing web application with latest technologies.
  • Well versed in a number of frameworks of Big Data Hadoop.
  • Demonstrates excellent programming skills.
  • Excellent training delivery skills with an ability to present information well.
  • Demonstrable proof of enthusiasm, initiative, creativity and problem solving.

Big Data Hadoop Instructor Experience

  • Writing reusable, testable, and efficient code
  • Designing and implementation of low-latency, high-availability, and performance applications.
  • Integration of user-facing elements developed by front-end developers with server side logic.
  • Integration of data storage solutions includes databases, key-value stores, blob stores, etc.
  • Developing back-end components to improve responsiveness and overall performance
  • Integrating user-facing elements into applications
  • Improving functionality of existing systems
  • Implementing security and data protection solutions

Apponix Ratings

apponix +11000 Satisfied Learners









Big Data training in Chennai

Apponix offers the best Big Data training in Chennai with most efficient and incredible features. We regularly follow the recent trends and requirements of the industry.

Student Review

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Kalpita Pakhare

Good trainer and helped a lot. He explained many real-time scenarios to understand the topics. Had a good learning experience..

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Khalid Naik

The way of teaching was very effective. The trainer supported very much. Complex concepts are taught in a very simple way.

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Kiran Maibr

Apponix was the best choice I have made. Good knowledge about the advanced technicalities was made. By the completion of the course, we will get a good idea about the basics and advanced technologies.

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Krishna Veni

i completed SEO course here .Akash sir is an excellent trainer! I had a great experience learning here!

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Kshira Poral

Apponix the one of the best institute for Digital Marketing and SEO. The way of teaching by Akash sir is fantastic, here i learned many things.

Salary expectation after completing course

The requirement for skilled and certified professionals in the field is increasing considerably. This results in a constant rise in the salary too. According to, the average annual salary of a Big Data professional is about INR 7.5 lakhs.

Career Expectation

Chennai is one of the most progressing technical markets in India. We offer here 100% job oriented training in Big Data. No worries about the placement, since this is one of the most promising careers of the 21st century with numerous opportunities and roles all over.

Why Should You Learn Big Data?

  • Most demanding and promising career option
  • Implementation in the fields of AI, Robotics, Web Development, DevOps and so on, has considerably increased the credibility and demand of Big Data Hadoop
  • It is one among the very few languages that is preferred by the most, premier, flexible, and of open source.
  • It is easy to learn and easy to use.
  • Accessibility to the powerful libraries of Big Data for the manipulation and analysis of data

Best Big Data Training in Chennai

  • Apponix offers the best Big Data training in Chennai with more efficient and incredible features.
  • We regularly follow the recent trends and requirements of the industry
  • Chennai offers the quick possibility of placement by N number of enterprises in the field
  • Excellent salary package and working condition are offered than in other places
  • Trainer with minimum a decade of experience
  • Flexible timings


  • Why should I choose Apponix for the trainng?
    • Complete hands-on training
    • Expert faculty
    • 2000+ students were trained
    • 5 star rated training
    • 100% job oriented training
    • Own study materials prepared by subject experts
    • Resume preparation
    • Prepares you to face any post training interview
    • Flexible timings
    • Learner-friendly infrastructure
    • Customised syllabus by experts in the field through in-depth research
  • Who can take the training?
    • Fresher graduates who have completed Engineering
    • Data Engineer
    • Software Developers
    • Software Architects
    • Project Managers
    • Data Analysts
    • Business Intelligence Professionals
    • ETL and Data Warehousing Professionals
    • DBAs and DB professionals
  • What is the duration of the training?
    • Approximately 40 hours
  • Which are the major companies that offer placements after the training?
    • Google
    • Facebook
    • Amazon
    • Infosys
    • CTS
    • TCS
    • Capgemini
  • What are the prominent job-roles related to the course?
    • Big Data Hadoop Administrator
    • Big Data Hadoop Engineer
  • Why to Choose Apponix?
    • Excellent and qualified trainers
    • Dedicated HR team & 1000+ placements
    • 7000+ happy students.
    • Excellent lab facility & AC classrooms.
    • 100% student satisfaction rate.