This document outlines the topics covered in a big data analytics training course, including an introduction to big data and Hadoop, the Hadoop ecosystem concepts, MapReduce concepts, Pig concepts, Hive concepts, Oozie workflow concepts, HBASE concepts, and real-life use cases. It also lists specific topics that will be covered such as the history of Hadoop, Hadoop ecosystems, HDFS, MapReduce statistics, understanding clusters, typical workflows, writing and reading files from HDFS, rack awareness, and developing MapReduce applications.

1. big data analytics training
Course Objective Summary
*During this course, you will learn
*Introduction to Big Data and
Hadoop.
*Hadoop ecosystem – Concepts.
* Hadoop Map-features reduce
concepts and

2. big data analytics training
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3. big data analytics training
• ADpevpelilcoaptiinogn st he map-reduce
• Pig concepts
• Hive concepts
• Oozie workflow concepts
• HBASE Concepts
• Real Life Use Cases

4. big data analytics training
• Introduction to Big Data and
• Hadoop
• What is Big Data?
• bWigh adta atare?
• the challenges for processing
• What technologies support big data?
• What is Hadoop?
• Why Hadoop?

5. big data analytics training
• Use Cases of Hadoop
• Histiry of Hadoop
• Hadoop eco systems
• Hdfs
• Map reduce
• Statistics

6. big data analytics training
• Understanding the Cluster
• Typical workflow
• Writing files to HDFS
• Reading files from HDFS
• Rack Awareness

7. big data analytics training
• Let's talk Map Reduce
• Before Map reduce
• Map Reduce Overview
• Word Count Problem
• Word Count Flow and Solution
• Map Reduce Flow
• pArlgoobrleitmhms s

8. big data analytics training
• Developing the Map Reduce
• Application
• Data Types
• File Formats