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Big Data Analytics with Hadoop

 

Please Note: All below course content will be covered in practical scenarios and regular assignments will be shared. All sessions will be recorded and shared with student for future reference (free of cost). Along with below course.

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 1: Introduction

  1. Lecture 1: What is Big Data
  2. Lecture 2: What is Hadoop
  3. Lecture 3: Distributed System and Hadoop
  4. Lecture 4: RDBMS and Hadoop

Section 3: UNDERSTANDING MAPREDUCE

  1. Lecture 14: How Map Reduce Works
  2. Lecture 15: Data flow in Map Reduce
  3. Lecture 16: Map operation
  4. Lecture 17: Reduce operation
  5. Lecture 18: Map Reduce Program In JAVA using Eclipse
  6. Lecture 19: Counting words with Hadoop—Running your first program
  7. Lecture 20: Writing Map Reduce Drivers, Mappers and Reducers in Java
  8. Lecture 21: Real-world “Map Reduce� problems
  9. Lecture 22: Hands-On Exercise: Writing a Map Reduce Program and Running a Map Reduce Job
  10. Lecture 23: Java Word Count Code Walkthrough
  11. Section Quiz

Section 5: Hive

  1. Lecture 28: Installation of Hive
  2. Lecture 29: Introduction to Apache Hive
  3. Lecture 30: Getting data into Hive
  4. Lecture 31: Hive’s Architecture
  5. Lecture 32: Hive-HQL
  6. Lecture 33: Query Execution
  7. Section Quiz

Section 7: Pig

  1. Lecture 37: Introduction and Installation of Pig
  2. Lecture 38: Pig Architecture
  3. Lecture 39: Pig Latin – Reading and writing data using Pig

Section 2: Starting Hadoop

  1. Lecture 5: Single node Hadoop Cluster
  2. Lecture 6: Configuring Hadoop
  3. Lecture 7: Hadoop Architecture
  4. Lecture 8: Hadoop Components
  5. Lecture 9: Name and Data Nodes
  6. Lecture 10: Command Line Interface
  7. Lecture 11: Running Hadoop
  8. Lecture 12: Web-based cluster UI-Name Node UI, Map Reduce UI
  9. Lecture 13: Hands-On Exercise: Using HDFS commands
  10. Section Quiz

Section 4: Hadoop Ecosystem

  1. Lecture 24: Hive
  2. Lecture 25: Sqoop
  3. Lecture 26: Pig
  4. Lecture 27: Hbase
  5. Section Quiz

Section 6: Sqoop

  1. Lecture 34: Installing and Configure Sqoop
  2. Lecture 35: Import RDBMS data to Hive using Sqoop
  3. Lecture 36: Export from to Hive to RDBMS using Sqoop

Section 8: HBase

  1. Lecture 40: Installation
  2. Lecture 41: Architecture of Hbase
  3. Lecture 42: Managing large data sets with HBase
  4. Final Quiz
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Students Testimonials

  • Seeing the demand of Python in programming, I decided to enroll for weekend classes of Python then after joining, Ankit sir took our class and from the beginning we attended all the classes..

    gaurav saini

  • Ankit sir is one of the best mentors I have ever had and he's supportive also . He's is the professional in every branch he know and....

    Anshul

  • Ankit sir is the best trainer and have best knowledge in coding he is the best teacher and also supports the idea help to develop them

    rishabh jain
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