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Artificial Intelligence & Data Science, VIII-Semester
AD-801 Big Data
Syllabus
Unit I: Introduction to Big data, Big data characteristics, Types of big data, Traditional versus Big data, Evolution of Big data, challenges with Big Data, Technologies available for Big Data, Infrastructure for Big data, Use of Data Analytics, Desired properties of Big Data system.
Unit II: Introduction to Hadoop, Core Hadoop components, Hadoop Eco system, Hive Physical Architecture, Hadoop limitations, RDBMS Versus Hadoop, Hadoop Distributed File system, Processing Data with Hadoop, Managing Resources and Application with Hadoop YARN, MapReduce programming.
Unit III: Introduction to Hive, Hive Architecture, Hive Data types, Hive Query Language, Introduction to Pig, Anatomy of Pig, Pig on Hadoop, Use Case for Pig, ETL Processing, Data types in Pig, running Pig, Execution model of Pig, Operators, functions, Data types of Pig.
Unit IV: Introduction to NoSQL, NoSQL Business Drivers, NoSQL Data architectural patterns, Variations of NoSQL architectural patterns using NoSQL to Manage Big Data, Introduction to MongoDB.
Unit V: Mining social Network Graphs: Introduction Applications of social Network mining, Social Networks as a Graph, Types of social Networks, Clustering of social Graphs Direct Discovery of communities in a social graph, Introduction to recommender system.
Text Books:
1. Radha Shankarmani, M. Vijaylakshmi, " Big Data Analytics", Wiley, 2 ndEdition
2. Seema Acharya, SubhashiniChellappan, " Big Data and Analytics", Wiley, 1 stEdition
3. Raj Kamal, PreetiSaxena, “Big Data Analytics, Introduction to Hadoop, Spark, and Machine-Learning”, McGraw Hill Education; First Edition,2019.
Reference Books:
1. KaiHwang, Geoffrey C., Fox. Jack, J. Dongarra, “Distributed and Cloud Computing”, Elsevier, First Edition
2. Michael Minelli, Michele Chambers, AmbigaDhiraj, “Big Data Big Analytics”, Wiley.
Notes
Assignment
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