Page 73 - B.Tech IT Curriculum and Syllabus R2017 - REC

Department of IT, REC

4. Illustrate the fundamental cloud computing mechanism with which cloud data centres are
managed and administered.
5. Analyse the core issue of cloud such as security, energy efficiency and interoperability, and
provide an insight into future prospects of computing in the cloud.

TEXT BOOKS:
1. Thomas Erl, Zaigham Mahood, Ricardo Puttini ―Cloud Computing, Concept, Technology
and Architecture‖, Prentice Hall, First Edition, 2013.
2. Kai Hwang, Geoffery C. Fox and Jack J. Dongarra, Distributed and Cloud Computing:
Clusters, Grids, Clouds and the Future of Internet, First Edition, Morgan Kaufman Publisher,
an Imprint of Elsevier, 2012.

REFERENCES:
1. Michael J. Kavis Architecting the Cloud: Design Decisions for Cloud Computing Service
Models (SaaS, PaaS, and IaaS), First Edition, Wiley.
2. Tom White, Hadoop: The Definitive Guide, Yahoo Press, 2014.
3. Rajkumar Buyya, Christian Vecchiola, and Thamarai Selvi, Mastering Cloud Computing,
Tata McGraw Hill, 2013.
4. John W.Rittinghouse and James F.Ransome, Cloud Computing: Implementation,
Management, and Security, CRC Press, 2010.

IT17701 DATA ANALYTICS L T P C
3 0 0 3
OBJECTIVES:

The student should be made to:
 To introduce the concepts of Big Data and Hadoop
 To help understand HDFS and Mapreduce concepts
 To imbibe the Hadoop Eco System of NoSQL
 To describe the data stream analytics methodologies
 To narrate various data analysis techniques

UNIT I INTRODUCTION TO BIG DATA AND HADOOP 6
Introduction to Big Data, Types of Digital Data, Challenges of conventional systems - Web data,
Evolution of analytic processes and tools, Analysis Vs reporting - Big Data Analytics, Introduction to
Hadoop - Distributed Computing Challenges - History of Hadoop, Hadoop Eco System.

UNIT II HDFS (HADOOP DISTRIBUTED FILE SYSTEM) AND MAP REDUCE 6
Hadoop Overview – Use case of Hadoop – Hadoop Distributors – HDFS – Processing Data with
Hadoop – Map Reduce - Managing Resources and Applications with Hadoop YARN – Interacting
with Hadoop Ecosystem.

UNIT III NOSQL DATABASES 12
NoSQL - Pig - Introduction to Pig, Execution Modes of Pig, Comparison of Pig with Databases,
Grunt, Pig Latin, User Defined Functions, Data Processing operators - Hive - Hive Shell, Hive
Services, Hive Metastore, Comparison with Traditional Databases, HiveQL, Tables, Querying –
MongoDB - Needs-Terms-Data Types-Query Language – Cassandra -Introduction-Features-Querying
Commands.

Curriculum and Syllabus | B.Tech. Information Technology | R2017 Page 73