Enter your keyword

BIG DATA

BIG DATA – HADOOP TRAINING COURSE

Big data simply means large amount of data. This data is so huge that it is not possible for comprehend or work on it. Hadoop is a technology that has emerged as the frontrunner for handling Big Data processing. Hadoop platform helps in storing, handling and retrieving enormous amounts of data in a variety of applications while also helping in deep analytics. As more and more companies are embracing Hadoop, the demand for Hadoop Developers is increasing. DigitalKul’s training on Big Data handling through Hadoop will help you understand the best ways of handling, processing and using large amount of data.

On successful completion of the course, you will receive a certification on Big Data from DigitalKul. In the course you will learn the following:

  • Understanding what Big Data is and how Hadoop is used to benefit out of the data?
  • Learn best practices and considerations for Hadoop development, debugging techniques and implementation of workflows and common algorithms
  • Learn how to use Hadoop frameworks like ApachePig, ApacheHive, Sqoop and Flume and other projects from the Apache Hadoop Ecosystem
  • Perform real-world analytics by learning advanced Hadoop API topics

BIG DATA HADOOP COURSE CURRICULUM

  • What is Big Data?
  • Big Data Use Cases
  • Scope of Big Data
  • What are the Drawbacks of Big Data
  • Advantages of Big Data
  • What is Hadoop?
  • Benefits of Hadoop
  • Where we isHadoop useful?
  • Hadoop History
  • Disadvantages of Hadoop
  • Hadoop Architecture
  • Industrial Use of Hadoop
  • Hadoop v/s other Big data tools
  • Hadoop Core Components
  • Hadoop Services
  • What are Master Services
  • What are Slave Services
  • Working of Name Node, Secondary Node, Job Traker
  • Working of Data Node, Task Tracker
  • Differences in Between Hadoop X .1 and Hadoop X. 2
  • Differences Between Linux and Windows setup
  • Setup Of Hadoop Single machine on Linux
  • Configuration of Hadoop
  • Importance of XML files in Hadoop
  • How to configure XML files
  • How to setup replication, block Size etc.
  • How to create Namenode And DataNode
  • How to check Services running or Not
  • How to Start and Stop Hadoop
  • Introduction of Map reduce
  • Internal Working of Map reduce
  • Mapper & Reduce
  • How file break into Mapper
  • How Mapper read a file using
  • What is the Work of Record Reader & RW
  • Use of Combiner and Partitioned in MR
  • Advantage of MR
  • Disadvantages of MR
  • Why we Use YARN
  • Word count Program
  • Hands on Practical
  • Understanding of hive and Importance of Hive
  • DatawareHouse AND RDBMS
  • Hive Aricturcture and Implementation Modes of Hive
  • DDL and DML Commands
  • Data Partitioning and Query Optimization
  • Buckets performance of data query
  • Practical hands-on
  • 1 minor project
  • What is Pig
  • Understanding of Pig and Importance of Pig
  • Pig AND RDBMS AND HIVE
  • Hive Aricturcture and Implementation Modes of Pig
  • Running and managing pig script
  • Perform Streaming Data Analysis Through Pig
  • Pig Advantage and Disadvantage
  • Project on Pig
  • What is sqoop
  • How to Use, advantages and Disadvantages of sqoop
  • Importing Data RDBMS TO HDSF “locally”
  • Exporting Data HDFS to RDBMS “locally”
  • Importing Data Other OS TO  HDFS
  • Exporting Data Other OS to RDBMS
  • What is flume
  • Advantages ,how we use flume
  • How to get data to HDFS
  • Flume API
  • How to convert Data Structure type

BRIEF COURSE AND COMMERCIAL DETAILS ARE AS BELOW:

  • Course Duration: 1 Month
  • Approximate training period: : 30 hours
  • Fees: INR 19,900
  • Sessions: Weekends/Weekdays
  • Number of modules covered: 9 modules
  • Learning method: Offline/Online

Leave your details below, we will contact you soon


Corporate Digital Marketing Training