Section- 1

• DW Definition
• DW Architecture
• Operation Data Bases(ODB)
• Data Modeling 3NF
  and Dimensional Modeling
• OLTP and OLAP
• ETL concepts
• Top Down/Bottom up approaches
• Bill Inmon approach – advantages
  and disadvantages
• Ralph Kimbell approach – advantages
  and disadvantages
• Star and Snowflake schemas
• Dimension modeling design considerations
• Normalization techniques with live examples
• Data Mart project examples
• Customer, Products, Geo dimensional concepts
• Hierarchy structures
• Master Data Management systems
• Information Management systems
• NO SQL – BIG Data
• ACID Model
• CAP Model

Section- 2

• HADOOP Architecture
• HDFS Architecture
• HDFS Features
• Intro Name node & Data Node
• File storage & Replication
• Build HADOOP Cluster–EC2/AWS
• Hadoop Configuration

Section- 3

• MapReduce Features
• MapReduce Job recovery
• MapReduce Job Check
• Cluster Rebalancing
• Secondary Name Node features
• Practice Hadoop Commands

Section- 4

• Introduction to Hive
• Installation of Hive
• Hive SQLs

• Hive internal and external tables
• Hive Partitions
• Introduction to SQOOP
• Installation of Sqoop
• Sqoop practice with Hadoop and HBase

  Section- 5

• Introduction to Pig
• Installation of Pig
• Pig Relations, Bags, Tuples, Fields
• Pig- expressions
• Pig- Schemas
• Pig- Join and Split Optimization
• Pig- JSON

   Section- 6

• Introduction to HBASE
• Architecture
• Install Hbase
• Region Servers , Master
• Hbase with Hive
• Hbase with Sqoop
• Hbase with PIG
• Hbase practice

Section- 7

• Installation on VM Ware
• Installation of CDH4

Section- 8

• Performance Tuning
• Certification discussion – CCA-410
• Practical Example

Each Day includes Theory and Lab practice

• Examples based on theory
• Exercises