IBM BigInsights Foundation (DW613G) – Outline

Detailed Course Outline

(DW6A1)

  • Unit 1: Introduction to Big Data
  • Exercise 1: Setting up the lab environment
  • Unit 2: Introduction to IBM BigInsights
  • Exercise 2: Getting started with IBM BigInsights
  • Unit 3: IBM BigInsights for Analysts
  • Exercise 3: Working with Big SQL and BigSheets
  • Unit 4: IBM BigInsights for Data Scientist
  • Exercise 4: Analyzing data with Big R, Jaql, and AQL
  • Unit 5: IBM BigInsights for Enterprise Management

(DW6B1)

  • Unit 1: IBM Open Platform with Apache Hadoop
  • Exercise 1: Exploring the HDFS
  • Unit 2: Apache Ambari
  • Exercise 2: Managing Hadoop clusters with Apache Ambari
  • Unit 3: Hadoop Distributed File System
  • Exercise 3:  File access & basic commands with HDFS
  • Unit 4: MapReduce and Yarn
  • Topic 1:  Introduction to MapReduce based on MR1
  • Topic 2:  Limitations of MR1
  • Topic 3:  YARN and MR2
  • Exercise 4: Creating and coding a simple MapReduce job (Possibly a more complex second Exercise)
  • Unit 5: Apache Spark
  • Exercise 5: Working with Sparks RDD to a Spark job
  • Unit 6: Coordination, management, and governance
  • Exercise 6: Apache ZooKeeper, Apache Slider, Apache Knox
  • Unit 7: Data Movement
  • Exercise 7: Moving data into Hadoop with Flume and Sqoop
  • Unit 8: Storing and Accessing Data
  • Topic 1:  Representing Data:  CSV, XML, JSON, and YAML
  • Topic 2:  Open Source Programming Languages: Pig, Hive, and Other [R, Python, etc]
  • Topic 3:  NoSQL Concepts
  • Topic 4:  Accessing Hadoop data using Hive
  • Exercise 8: Performing CRUD operations using the HBase shell
  • Topic 5:  Querying Hadoop data using Hive
  • Exercise 9:  Using Hive to Access Hadoop / HBase Data
  • Unit 9: Advanced Topics
  • Topic 1: Controlling job workflows with Oozie
  • Topic 2: Search using Apache Solr
  • No lab exercises