Course Name: 

Big Data Analytics (IT438)


B.Tech (AI)


Programme Specific Electives (PSE)

Credits (L-T-P): 

(3-0-2) 4


Introduction– distributed file system–Big Data and its importance, Four Vs, Drivers for Big data, Algorithms using map reduce, Apache Hadoop & Hadoop EcoSystem, Data Serialization, HDFS, Hive Architecture, HiveQL Querying Data, Sorting And Aggregating, Map Reduce Scripts, Joins & Sub queries, HBase concepts, Schema Design, Advance Indexing, PIG, Zookeeper , Data Analysis with Spark, Programming with RDDs, Machine Learning with MLlib, NoSQL, NewSQL, Creating and Querying through Indexes, Document-Oriented, principles of schema design, Constructing queries on Databases, collections and Documents, MongoDB Query Language, Big data analytics, Big data applications.


Understanding Big data, Chris Eaton,Dirk derooset al, McGraw Hill, (2017)
Big Data and Analytics, 2ed, Subhashini Chellappan Seema Acharya, Wiley (2019)
Big Data: Principles and Best Practices of Scalable Real-Time Data Systems - Nathan Marz and James Warren, Manning Publishers (2015)


Information Technology

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Head of the Department,
Department of Information Technology,
National Institute of Technology Karnataka,
SurathkalP. O. Srinivasnagar, Mangalore - 575 025
Ph.:    +91-824-2474056
Email:  hodit [at] nitk [dot] edu [dot] in

Web Admin: Sowmya Kamath S

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