Big Data Analytics detailed syllabus for Computer & Communication Engineering (CCE) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the CCE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Computer & Communication Engineering 5th Sem scheme and its subjects, do visit CCE 5th Sem 2021 regulation scheme. For Professional Elective-I scheme and its subjects refer to CCE Professional Elective-I syllabus scheme. The detailed syllabus of big data analytics is as follows.
Course Objectives:
Download the iStudy App for all syllabus and other updates.
Unit I
UNDERSTANDING BIG DATA
Introduction to big data – convergence of key trends – unstructured data – industry examples of big data – web analytics – big data applications- big data technologies – introduction to Hadoop – open source technologies – cloud and big data – mobile business intelligence – Crowd sourcing analytics – inter and trans firewall analytics.
Unit II
NOSQL DATA MANAGEMENT
Introduction to NoSQL – aggregate data models – key-value and document data models -relationships – graph databases – schemaless databases – materialized views – distribution models – master-slave replication – consistency – Cassandra – Cassandra data model – Cassandra examples – Cassandra clients
Unit III
Download the iStudy App for all syllabus and other updates.
Unit IV
BASICS OF HADOOP
Data format – analyzing data with Hadoop – scaling out – Hadoop streaming – Hadoop pipes -design of Hadoop distributed file system (HDFS) – HDFS concepts – Java interface – data flow -Hadoop I/O – data integrity – compression – serialization – Avro – file-based data structures -Cassandra – Hadoop integration.
Unit V
HADOOP RELATED TOOLS
Hbase – data model and implementations – Hbase clients – Hbase examples – praxis.
Pig – Grunt – pig data model – Pig Latin – developing and testing Pig Latin scripts.
Hive – data types and file formats – HiveQL data definition – HiveQL data manipulation – HiveQL queries.
Course Outcomes:
After the completion of this course, students will be able to:
- Describe big data and use cases from selected business domains.
- Explain NoSQL big data management.
- Install, configure, and run Hadoop and HDFS.
- Perform map-reduce analytics using Hadoop.
- Use Hadoop-related tools such as HBase, Cassandra, Pig, and Hive for big data analytics.
List of Experiments:
Download the iStudy App for all syllabus and other updates.
Text Books:
- Michael Minelli, Michelle Chambers, and AmbigaDhiraj, “Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Businesses”, Wiley, 2013.
- Eric Sammer, “Hadoop Operations”, O’Reilley, 2012.
- Sadalage, Pramod J. “NoSQL distilled”, 2013
Reference Books:
- E. Capriolo, D. Wampler, and J. Rutherglen, “Programming Hive”, O’Reilley, 2012.
- Lars George, “HBase: The Definitive Guide”, O’Reilley, 2011.
- Eben Hewitt, “Cassandra: The Definitive Guide”, O’Reilley, 2010.
- Alan Gates, “Programming Pig”, O’Reilley, 2011.
For detailed syllabus of all the other subjects of Computer & Communication Engineering 5th Sem, visit CCE 5th Sem subject syllabuses for 2021 regulation.
For all Computer & Communication Engineering results, visit Anna University CCE all semester results direct link.