Big Data & Hadoop Course

by DigiStacKedu Claim Listing

Big Data is all about distributed data processing and it is an emerging field in the current IT sector, professionals are using hadoop for processing huge amount of data that is stored on various RDBMS and company servers.this course will upgrade your skills in apache spark.

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DigiStacKedu without logo

img Duration

3 Months

Course Details

Big Data is all about distributed data processing and it is an emerging field in the current IT sector, professionals are using hadoop for processing huge amount of data that is stored on various RDBMS and company servers.this course will upgrade your skills in apache spark, python, scala and ETL operations uisng sqoop moreover, you will learn how real time data is processed using apache kafka.

After completion of this course you'll be able to work on big data tools moreover,you will be an expert of python and scala programming language.In this couse you will learn how to do distributed data processing using python and scala.

We will start this course with basics of Hadoop and its architecture then you will work on hadoop advance level Tools like Apache Sqoop and Apache Hive that is required to process big data,you will learn how to analyze different types of data sets and how ot visualize and generate reports.

 

Course Syllabus:

  • Module 1: Introduction to Big Data & Hadoop
  • Introduction to big data and its background.
  • Understading the role of Hadoop Framework.
  • A Brief History of Distributed Computing.
  • Understanding the Basics of Distributed Computing.
  • Understading Data Warehouses and its role.
  • Understading Big Data vs Traditional Data Warehouse Systems.
  • Introduction to RDBMS.
  • Working on IBM DB2 or Mysql.
  • Working on DB2/Mysql Databases and Tables.
  • DB2/Mysql Hands on Lab.
  • Understanding RDBMS in a Big Data Environment
  • Module 2: Installation and Configuration of Big Data tools.
  • Module 3: Hadoop Distributed File System.
  • Module 4: Map Redduce - A Distributed Architecture
  • Module 5: Data Warehousing using Hive.
  • Module 6: ETL - Working on Sqoop and Flume
  • Module 7: Big Data Processing Using Apache PIG.
  • Module 8: Working on Apache Spark Using Scala and Python.
  • Module 9: Apache Spark Transformations and Actions.
  • Module 10: Apache YARN and Spark SQL.
  • Module 11: Working on DataFrames in Spark SQL.
  • Module 12: Apache Spark Streaming and Apache Kafka.
  • Module 13: Real Time Project Development in Big Data.
  • Kanpur Branch

    First Floor, C-40, Dashmesh Nagar Road, Kanpur

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