MSC Semester III - Big Data Analytics

Unit - |

overview of Big Data: what is Big Data Evolution ol'Big Data, Structuring Big Data, Elements ol

Big Data. I3ig Data Analytics. Exploring the Use ol Big Data in Business Context: Use of Big Data

in Social Networking. Use of Big Data in Preventing Fraudulent Activities, Use of Big Data in

Detecting Fraudulent Activities in the Insurance Sector. Use of Big Data in Retail Industry.

introducing Technologies for Handling Big Data: Distributed and Parallel Computing for Big Data.

introducing Hadoop. Understanding Hadoop Ecosystem: Hadoop Ecosystem. HDFS, Map Reduce.

Hadoop YARN. HBase. Hive, Pig and Pig Latin, Sqoop. ZooKeeper, Flume, Oozie.

Unit - II

understanding MapReduce Fundamentals and HBase: The MapReduce Framework, Techniques to

optimize MapRedr.rce Jobs. Role of HBase in Big Data Processing. Exploring the Big Data Stack,

Virtualization and Big Data, Virtualization Approaches.

Storing Data in Databases and Data warehouses: RDBMS and Big Data, Non-Relational Database,

integrating Big Data with traditional Data warehouses. Big Data Analysis and Data warehouse,

Changing Deployment Models in Big Data Era.

Processing Your Data with MapReduce: Developing Simple MapReduce Application points to

Consider while Design in MapReduce.

customizing MapReduce Execution: controlling MapReduce Execution with InputForrnat,

Reading Data with Custom RecordReader. organizing output Data

customizing Data with Recordwriter. optimizing MapReduce Execution* with combiner,

implementing a MapReduce Program for Soning Text Data.

Llnit - lll

Understanding Hadoop YARN Architecture: introduction yARN, Advantages of yARN, yARN

Architecture. Working of YARN.

Exploring Hive: Introducing Hive, getting Started '" with Hive, Hive Services, Data Types in Hive,

Builrln Functions in Hive. Hive DDL, Data Manipulation irr Hive, Data Retrieval queries, Using

.lOlNS in Hive.

Analyzing Data with Pig: Introducing Pig, Running pig. catering Starred with pig Latin, working

with operators in Pig. working with Functions in Pig, Debugging Pig, and Error Handling in pig.

Unit - IV

Usingoozie: introducing oozie, installing and configuring oozie, understanding the oozie

Workfl ow. Simple Application.

NoSQL Data Management: introduction to NoSQL, Types of NoSeL Data Models, Schenra-Less

Databases. Materialized views. Distributed Models. Sharding. MapReduce partitioning and

Combining. Composing MapReduce Calculations.

Understanding Analytics and Big Data: Conrparing Reponing and Analysis, Types of Analytics.

Developing an Analytic Team. Analytical Approaches and tools to Analyze Data: Analytical

Approaches. History of Analytical Tools, Introducing Analytical Tools, Comparing Various