Faculty of Engineering, OU B.E.(I.T.) w.e.f.
2023 - 2024
BIG DATA ANALYTICS (PC702IT)
Instruction : 3 periods per week Duration of SEE : 3 hours
CIE : 30 marks SEE : 70 marks Credits : 3
Course Objectives:
1. Understand big data for business intelligence.
2. Identify business case studies for big data analytics.
3. Defend big data Without SQL.
4. Discuss the process of data analytics using Hadoop and related tools.
Course Outcomes:
1. Demonstrate big data and use cases from selected business domains.
2. Apply the knowledge of NoSQL big data management and experiment with Install, configure, and run Ha
3. Analyse map-reduce analytics using Hadoop.
4. Adapt Hadoop related tools such as HBase, Cassandra, Pig, and Hive for big data Analytics.
UNIT-I
Understanding Big Data: Characteristics of Data, Introduction to Big Data and its importance,
Challenges posed by Big Data, Big data analytics and its classification, Big data applications: big
data and healthcare - big data in banking - advertising and big data, big data technologies.
UNIT-II
Hadoop Distributed File System: Hadoop Ecosystem, Hadoop Architecture, HDFS Concepts,
Blocks, Namenodes and Datanodes, Hadoop FileSystems, The Java Interface, Reading Data from a
Hadoop URL, Writing Data, Querying the FileSystem, Deleting Data, Anatomy of File Read and
Write.
UNIT-III
NOSQL Data Management: Introduction to NOSQL - aggregate data models, aggregates key value
and document data models, relationships - graph databases, schema less databases, Sharding -
map reduce - partitioning and combining - composing map-reduce calculations.
UNIT-IV
Map Reduce and Yarn: Hadoop Map Reduce paradigm, Map and Reduce tasks, Job and Task
trackers, Mapper, Reducer, Map Reduce workflows, classic Map-reduce - YARN - failures in classic
Map-reduce and YARN - job scheduling - shuffle and sort - task execution - Map Reduce types -
input formats - output formats.
UNIT-V
Pig: Installing and Running Pig, an Example, Comparison with Databases, Pig Latin, User-Defined
Functions, Data Processing Operators. Hive: The Hive Shell, An Example, Running Hive,
Comparison with Traditional Databases, HiveQL, Tables, Querying Data, User-Defined Functions,
writing a User Defined Functions.
Suggested Reading:
1. Tom White, "Hadoop: The Definitive Guide", Third Edition, O'Reilly, 2012, ISBN -13:
978-1449311520, ISBN-10: 1449311520
2. Pramod Sadalage, Martin Fowler, "NoSQL Distilled - A brief guide to the emerging world of
polyglot", Addison Wesley 2013
3. Eric Sammer, "Hadoop Operations", O'Reilly, 2012, ISBN -13 978-1449327057, ISBN-10:
1449327052
4. Vignesh Prajapati, Big data analytics with R and Hadoop, 2013, ISBN -13: 978-1782163282
5. E. Capriolo, D. Wampler, and J. Rutherglen, "Programming Hive", O'Reilly, 2012, ISBN -13:
978-1449319335
