B.E. (Automation and Robotics) Big Data Analytics Syllabus - Mumbai University 2026

Database, Data mining.

Module 1: Introduction to Big Data and Hadoop

• Introduction to Big Data - Big Data characteristics and Types of Big Data Traditional vs. Big Data business approach Case Study of Big Data Solutions Concept of Hadoop, Core Hadoop Components; Hadoop Ecosystem

Module 2: Hadoop HDFS and MapReduce

• Distributed File Systems: Physical Organization of Compute Nodes, Large- Scale File-System Organization. MapReduce: The Map Tasks, Grouping by Key, The Reduce Tasks, Combiners, Details of MapReduce Execution, Coping With Node Failures. Algorithms Using MapReduce: Matrix-Vector Multiplication by MapReduce, Relational-Algebra Operations, Computing Selections by MapReduce, Computing Projections by MapReduce, Union, Intersection, and Difference by MapReduce, Hadoop Limitations.

Module 3: NoSQL

• Introduction to NoSQL, NoSQL Business Drivers. NoSQL Data Architecture Patterns: Key-value stores, Graph stores, Column family (Bigtable)stores, Document stores, Variations of NoSQL architectural patterns, NoSQL Case Study. NoSQL solution for big data, Understanding the types of big data problems; Analyzing big data with a shared-nothing architecture; Choosing distribution models: master-slave versus peer-to-peer; NoSQL systems to handle big data problems.

Module 4: Mining Data Streams

• The Stream Data Model: A Data-Stream-Management System, Examples of Stream Sources, Stream Queries, Issues in Stream Processing. Sampling Data techniques in a Stream. Filtering Streams: Bloom Filter with Analysis. Counting Distinct Elements i n a Stream, Count- Distinct Problem, Flajolet-Martin Algorithm, Combining Estimates, Space Requirements. Counting Ones in a Window: The Cost of Exact Counts, The Datar Gionis-Indyk-Motwani Algorithm, Query Answering in the DGIM Algorithm, Decaying Windows.

Module 5: Real-Time Big Data Models

• A Model for Recommendation Systems, Content-Based Recommendations, Collaborative Filtering. Case Study: Product Recommendation Social Networks as Graphs, Clustering of Social-Network Graphs, Direct Discovery of Communities in a social graph

Module 6: Data Analytics with R

• Exploring Basic features of R, Exploring RGUI, Exploring RStudio, Handling Basic Expressions in R, Variables in R, Working with Vectors, Storing and Calculating Values in R, Creating and using Objects, Interacting with users, Handling data in R workspace, Executing Scripts, Creating Plots, Accessing help and documentation in R. Reading datasets and Exporting data from R, Manipulating and Processing Data in R, Using functions instead of script, built-in functions in R. Data Visualization: Types, Applications

Text Books

• 1 Cre Anand Rajaraman and Jeff Ullman ―Mining of Massive Datasets‖, Cambridge University Press
• 2 Alex Holmes ―Hadoop in Practice‖, Manning Press, Dreamtech Press.
• 3 Dan Mcary and Ann Kelly ―Making Sense of NoSQL‖ – A guide for managers and the rest of us, Manning Press.
• 4 DT Editorial Services, “Big Data Black Book”, Dreamtech Press
• 5 EMC Education Services, ”Data Science and Big Data Analytics”, Wiley
• 1 Bill Franks, ―Taming The Big Data Tidal Wave: Finding Opportunities In Huge Data Streams With Advanced Analytics,Wiley.
• 2 Chuck Lam, ―Hadoop in Action, Dreamtech Press
• 3 Jared Dean, ―Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners, Wiley India Private Limited, 2014.
• 4 Jiawei Han and Micheline Kamber, ―Data Mining: Concepts and Techniques‖, Morgan Kaufmann Publishers, 3rd ed, 2010.
• 5 Lior Rokach and Oded Maimon, ―Data Mining and Knowledge Discovery Handbook, Springer, 2nd edition, 2010.
• 6 Ronen Feldman and James Sanger, ―The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data‖, Cambridge University Press, 2006.
• 7 Vojislav Kecman, ―Learning and Soft Computing, MIT Press, 2010.
• 1 https://nptel.ac.in/courses/106104189
• 2 https://www.coursera.org/specializations/big-data#courses
• 3 https://www.digimat.in/nptel/courses/video/106106169/L01.html
• 4 https://www.coursera.org/learn/nosql-databases#syllabus
• 5 https://www.coursera.org/learn/basic-recommender-systems#syllabus U University of Mumbai