• Comparison of traditional data management systems with Big Data management systems
• Evaluate key framework requirements for Big Data analytics
• Hadoop Ecosystem & Hadoop 2.x core components
• Explain the relevance of real-time data
• Explain how to use big and real-time data as a Business planning tool

Module 3:Hadoop Cluster -Architecutre - Configuration files

• Hadoop Master-Slave Architecture
• The Hadoop Distributed File System - data storage
• Explain different types of cluster setups(Fully distributed/Pseudo etc)
• Hadoop Cluster set up - Installation
• Hadoop 2.x Cluster Architecture
• A Typical enterprise cluster – Hadoop Cluster Modes

Module 4:Hadoop Core Components - HDFS & Map Reduce(YARN)

• HDFS Overview & Data storage in HDFS
• Get the data into Hadoop from local machine (Data Loading Techniques) - vice versa
• MapReduce Overview (Traditional way Vs. MapReduce way)
• Concept of Mapper & Reducer
• Understanding MapReduce program skeleton
• Running MapReduce job in Command line/Eclipse

• Develop MapReduce Program in JAVA
• Develop MapReduce Program with the streaming API
• Test and debug a MapReduce program in the design time
• How Partitioners and Reducers Work Together
• Writing Customer Partitioners Data Input and Output
• Creating Custom Writable and Writable Comparable Implementations

Module 5:Data Integration using Sqoop, Flume & Talend

• Integrating Hadoop into an existing Enterprise
• Loading Data from an RDBMS into HDFS by Using Sqoop
• Managing Real-Time Data Using Flume
• Accessing HDFS from Legacy Systems with FuseDFS and HttpFS
• Introduction to Talend (commuity system)
• Data loading to HDFS using Talend

Module 6:Data Analysis using PIG

• Introduction to Hadoop Data Analysis Tools
• Introduction to PIG - MapReduce Vs Pig, Pig Use Cases
• Pig Latin Program & Exectution
• Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Pig UDF
• Use Pig to automate the design and implementation of MapReduce applications
• Data Analysis using PIG

Module 7:Data Analysis using HIVE

• Introduction to Hive - Hive Vs. PIG - Hive Use Cases
• Discuss the Hive data storage principle
• Explain the File formats and Records formats supported by the Hive environment
• Perform operations with data in Hive
• Hive QL: Joining Tables, Dynamic Partitioning, Custom MapReduce Scripts
• Hive Script, Hive UDF

Module 8:Data Analysis using Impala

• Introduction to Impala & Architecture
• How Impala executes Queries and its importance.
• Hive vs. PIG vs. Impala
• Extending impala with User Defined functions
• Improving impala Performance

Module 9:NoSql Data base - HBASE

• Introduction to NoSQL Databases and Hbase
• HBase v/s RDBMS, HBase Components, HBase Architecture
• HBase Cluster Deployment

Module 10:Hadoop - Other Analytics Tools

• Introduction to role of R in Hadoop Eco-system
• Introduction to Jasper Reports & creating reports by integrating with Hadoop
• Role of Kafka & Avro in real projects