Instructorstat mat
TypeOnline Course
DateNov 18, 2017
PriceRs.20000
Buy NowBook Now

Big Data Analytics with Hadoop

As the need for big data analytics gains prominence world over; there is a subsequent growth in demand for Hadoop skill to process big data.
Program Objective

This course aims to take you through all the Big Data and Hadoop analytics concepts through step by step, well structured modules. It is our objective at Analytic square that by the end of this program you should be able to –

  • Have a basic understanding of Hadoop Distributed File System as well as MapReduce framework
  • Create a Hadoop cluster
  • Work with Sqoop and Flume on Data Loading Techniques
  • Learn to program in YARN, MapReduce and even write them
  • Do data analytics
  • Work on your own Big Data Analytics project implementing Hadoop

Who Should Join

If you are interested in big data and want to become a proficient Hadoop Developer this course is just right for you. You can benefit from this course if you are a –

  • Software professionals
  • ETL developers
  • Project Managers
  • Analytics Professionals
  • Testing experts
  • Students with knowledge of Core Java
Section 1Introduction
Lecture 1What is Big Data
Lecture 2What is Hadoop
Lecture 3Distributed System and Hadoop
Lecture 4RDBMS and Hadoop
Section 2Starting Hadoop
Lecture 5Single node Hadoop Cluster
Lecture 6Configuring HadoopFree Preview
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  2. Aenean eu leo quam. Pellentesque ornare sem lacinia quam venenatis vestibulum.
  3. Cras justo odio, dapibus ac facilisis in, egestas eget quam.
  4. Nulla vitae elit libero, a pharetra augue.
  5. Donec ullamcorper nulla non metus auctor fringilla.
  6. Nullam quis risus eget urna mollis ornare vel eu leo.

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Pharetra Malesuada Cursus Euismod
Ipsum Portalion Elitesimo Aenean
Ipsum Portalion Elitesimo Aenean
Ipsum Portalion Elitesimo Aenean
Ipsum Portalion Elitesimo Aenean
Ipsum Portalion Elitesimo Aenean
Nullam Sit Fringilla Malesuada

Donec sed odio dui. Fusce dapibus, tellus ac cursus commodo, tortor mauris condimentum nibh, ut fermentum massa justo sit amet risus. Cras justo odio, dapibus ac facilisis in, egestas eget quam. Praesent commodo cursus magna, vel scelerisque nisl consectetur et. Aenean eu leo quam. Pellentesque ornare sem lacinia quam venenatis vestibulum. Donec ullamcorper nulla non metus auctor fringilla. Duis mollis, est non commodo luctus, nisi erat porttitor ligul. Aeget lacinia odio sem nec elit. Vestibulum id ligula porta felis euismod semper. Duis mollis, est non commodo luctus, nisi erat porttitor ligula, eget lacinia odio sem nec elit.Nullam quis risus eget urna mollis ornare vel eu leo. Integer posuere erat a ante venenatis dapibus posuere velit aliquet. Donec sed odio dui. Aenean eu leo quam. Pellentesque ornare sem lacinia quam venenatis vestibulum.

Lecture 7Hadoop Architecture
Lecture 8Hadoop Components
Lecture 9Name and Data Nodes
Lecture 10Command Line Interface
Lecture 11Running Hadoop
Lecture 12Web-based cluster UI-Name Node UI, Map Reduce UI
Lecture 13Hands-On Exercise: Using HDFS commands
Section Quiz
Section 3UNDERSTANDING MAPREDUCE
Lecture 14How Map Reduce Works
Lecture 15Data flow in Map Reduce
Lecture 16Map operation Free Preview
Cum sociis natoque penatibus et magnis dimontes.


Nullam quis risus eget urna mollis ornare vel eu leo. Nullam quis risus eget urna mollis ornare vel eu leo. Praesent commodo cursus magna, vel scelerisque nisl consectetur et. Cras justo odio, dapibus ac facilisis in, egestas eget quam. Sed posuere consectetur est at lobortis. Sed posuere consectetur est at lobortis. Cras mattis consectetur purus sit amet fermentum. Etiam porta sem malesuada magna mollis euismod.

  1. Lorem ipsum dolor sit amet, consectetur adipiscing elit.
  2. Aenean eu leo quam. Pellentesque ornare sem lacinia quam venenatis vestibulum.
  3. Cras justo odio, dapibus ac facilisis in, egestas eget quam.
  4. Nulla vitae elit libero, a pharetra augue.
  5. Donec ullamcorper nulla non metus auctor fringilla.
  6. Nullam quis risus eget urna mollis ornare vel eu leo.
Pharetra Malesuada Cursus Euismod
Ipsum Portalion Elitesimo Aenean
Ipsum Portalion Elitesimo Aenean
Ipsum Portalion Elitesimo Aenean
Ipsum Portalion Elitesimo Aenean
Ipsum Portalion Elitesimo Aenean
Nullam Sit Fringilla Malesuada

Donec sed odio dui. Fusce dapibus, tellus ac cursus commodo, tortor mauris condimentum nibh, ut fermentum massa justo sit amet risus. Cras justo odio, dapibus ac facilisis in, egestas eget quam. Praesent commodo cursus magna, vel scelerisque nisl consectetur et. Aenean eu leo quam. Pellentesque ornare sem lacinia quam venenatis vestibulum. Donec ullamcorper nulla non metus auctor fringilla. Duis mollis, est non commodo luctus, nisi erat porttitor ligul.


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eget lacinia odio sem nec elit. Vestibulum id ligula porta felis euismod semper. Duis mollis, est non commodo luctus, nisi erat porttitor ligula, eget lacinia odio sem nec elit.Nullam quis risus eget urna mollis ornare vel eu leo. Integer posuere erat a ante venenatis dapibus posuere velit aliquet. Donec sed odio dui. Aenean eu leo quam. Pellentesque ornare sem lacinia quam venenatis vestibulum.

Lecture 17Reduce operation
Lecture 18Map Reduce Program In JAVA using Eclipse
Lecture 19Counting words with Hadoop—Running your first program
Lecture 20Writing Map Reduce Drivers, Mappers and Reducers in Java
Lecture 21Real-world "Map Reduce" problems
Lecture 22Hands-On Exercise: Writing a Map Reduce Program and Running a Map Reduce Job
Lecture 23Java Word Count Code Walkthrough
Section Quiz
Section 4Hadoop Ecosystem
Lecture 24Hive
Lecture 25Sqoop
Lecture 26Pig
Lecture 27Hbase
Section Quiz
Section 5Hive
Lecture 28Installation of Hive
Lecture 29Introduction to Apache Hive
Lecture 30Getting data into Hive
Lecture 31Hive's Architecture
Lecture 32Hive-HQL
Lecture 33Query Execution
Section Quiz
Section 6Sqoop
Lecture 34Installing and Configure Sqoop
Lecture 35Import RDBMS data to Hive using Sqoop
Lecture 36Export from to Hive to RDBMS using Sqoop
Section 7Pig
Lecture 37Introduction and Installation of Pig
Lecture 38Pig Architecture
Lecture 39Pig Latin - Reading and writing data using Pig
Section 8HBase
Lecture 40Installation
Lecture 41Architecture of Hbase
Lecture 42Managing large data sets with HBase
Final Quiz