Technology Consultant | AI | Data Science | Machine Learning

BIG DATA Analytics & Hadoop

  • Understand business analytics and big data technologies
  • Learning data mining concepts, techniques through an open source DM tool
  • Understand the role of big data technologies (Hadoop, HBase, Hive) in business analytics
  • Acquire the knowledge and learn to use Hadoop (HDFS and MapReduce), HBase and Hive

Course Curriculum

Module 1: Fundamentals of Big data
Module 2: Big Data Management
  • Distributed file systems for big data storage, access, and analytics
  • Frameworks and tools for big data cyber security analytics
  • Performance modelling, simulation and analysis
  • Big data applications in cyber security
  • Parallel and distributed algorithms for big data analytics
  • Big data case studies and applications
Module 3: HADOOP
  • Different Components of Hadoop
  • Introduction to Apache Pig
  • Map Reduce vs. Apache Pig
  • SQL vs. Apache Pig
  • Different Data Types in Pig
  • Modes of Execution in Pig
  • Execution Mechanism
  • Transformations in Pig
  • How to Write a Simple Pig script
  • UDFs in Pig
Module 4: HDFS (Hadoop Distributed File System)
  • Significance of HDFS in Hadoop
  • Features of HDFS
  • 5 daemons of Hadoop
Module 5: HIVE
  • HIVE Introduction
  • HIVE Architecture
  • HIVE Meta Store
  • HIVE Integration with Hadoop
Module 6: MAP REDUCE
  • MapReduce Architecture
  • MapReduce Programming Mode
  • Different Phases of MapReduce Algorithm
  • Different Data Types in MapReduce
  • How to Write a Basic MapReduce Program
  • Joining Datasets In MapReduce Jobs – Map Joins and Reduce Joins
  • Creating Input and Output Formats in MapReduce Jobs
  • How to Debug MapReduce Jobs in Local and Pseudo Cluster Mode
  • Data Localization in MapReduce
  • Combiner (Mini Reducer and Partitioner)
Module 7: Hbase
  • Overview
  • Instalation
  • Hbase Shell
  • Hbase General Camand
Module 8: Sqoop
  • What sqoop does
  • Data Imports
  • Parallel data transfer
  • Fast Data copies
  • Projects



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