Hadoop for Business Analysts

Course Number:


Apache Hadoop is the most popular framework for processing Big Data. Hadoop provides rich and deep analytics capability, and it is making in-roads into the traditional business intelligence and analytics world. This course will introduce an analyst to core components of the Hadoop ecosystem and its analytics.


This course is designed especially for business analysts.
Course Duration:
3 days


Participants should have a programming background with databases / SQL and a basic knowledge of Linux (e.g., be able to navigate Linux command line, editing files with vi / nano).

Course Objectives:
Course Outline:
  • Introduction to Hadoop
    • Hadoop History, Concepts
    • Ecosystem
    • Distributions
    • High-Level Architecture
    • Hadoop Myths
    • Hadoop Challenges
    • Hardware / Software


  • HDFS Overview
    • Concepts (Horizontal Scaling, Replication, Data Locality, Rack Awareness)
    • Architecture (NameNode, Secondary NameNode, Data Node)
    • Data Integrity
    • Future of HDFS (NameNode HA, Federation)
    • Lab Exercises


  • Map Reduce Overview
    • MapReduce Concepts
    • Daemons: JobTracker / TaskTracker
    • Phases: Driver, Mapper, Shuffle/Sort, Reducer
    • Thinking in MapReduce
    • Future of MapReduce (YARN)
    • Lab Exercises


  • Pig
    • Pig Versus Java MapReduce
    • Pig Latin Language
    • User-Defined Functions
    • Understanding Pig Job Flow
    • Basic Data Analysis with Pig
    • Complex Data Analysis with Pig
    • Multi Datasets with Pig
    • Advanced Concept
    • Lab Exercises


  • Hive
    • Hive Concepts
    • Architecture
    • Data Types
    • Hive Data Management
    • Hive Versus SQL
    • Lab Exercises


  • BI Tools for Hadoop
    • BI Tools and Hadoop
    • Overview of Current BI Tools Landscape


  • Conclusion
    • Choosing the Best Tool for the Job

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