MTech Advances In Data Base Management System syllabus for 2 Sem 2020 scheme 20SCE252

Module-1 Review of Relational Data Model and Relational Database Constraints 0 hours

Review of Relational Data Model and Relational Database Constraints:

Relational model concepts; Relational model constraints and relational database schemas; Update operations, anomalies, dealing with constraint violations, Types and violations.

 

Object and Object-Relational Databases:

Overview of Object Database Concepts, Object Database Extensions to SQL, The ODMG Object Model and the Object Definition Language ODL, Object Database Conceptual Design, The Object Query Language OQL, Overview of the C++ Language Binding in the ODMG Standard.

Module-2 Disk Storage, Basic File Structures, Hashing, and Modern Storage Architectures 0 hours

Disk Storage, Basic File Structures, Hashing, and Modern Storage Architectures:

Introduction, Secondary Storage Devices, Buffering of Blocks, Placing File Records on Disk Operations on Files, Files of Unordered Records (Heap Files) , Files of Ordered Records (Sorted Files), Hashing Techniques, Other Primary File Organizations, Parallelizing Disk Access Using RAID Technology, Modern Storage Architectures.

 

Distributed Database Concepts:

Distributed Database Concepts, Data Fragmentation, Replication, and Allocation Techniques for Distributed Database Design, Overview of Concurrency Control and Recovery in Distributed Databases, Overview of Transaction Management in Distributed Databases,Query Processing and Optimization in Distributed Databases, Types of Distributed Database Systems , Distributed Database Architectures, Distributed Catalog Management.

A d v e r t i s e m e n t
Module-3 NOSQL Databases and Big Data Storage Systems 0 hours

NOSQL Databases and Big Data Storage Systems:

Introduction to NOSQL Systems, The CAP Theorem, Document-Based NOSQL Systems and MongoDB, NOSQL Key-Value Stores, Column-Based or Wide Column NOSQL Systems, NOSQL Graph Databases and Neo4j.

 

Big Data Technologies Based on MapReduce and Hadoop:

What Is Big Data? Introduction to MapReduce and Hadoop, Hadoop Distributed File System (HDFS), MapReduce: Additional Details Hadoop v2 alias YARN, General Discussion

Module-4 Enhanced Data Models 0 hours

Enhanced Data Models: Introduction to Active, Temporal, Spatial, Multimedia, and Deductive Databases:

Active Database Concepts and Triggers, Temporal Database Concepts, Spatial Database Concepts, Multimedia Database Concepts, Introduction to Deductive Databases.

 

Introduction to Information Retrieval and Web Search:

Information Retrieval (IR) Concepts, Retrieval Models, Types of Queries in IR Systems, Text Preprocessing, Inverted Indexing, Evaluation Measures of Search Relevance, Web Search and Analysis. Trends in Information Retrieval

Module-5 Data Mining Concepts 0 hours

Data Mining Concepts:

Overview of Data Mining Technology, Association Rules, Classification, Clustering, Approaches to Other Data Mining Problems, Applications of Data Mining, Commercial Data Mining Tools

 

Overview of Data Warehousing and OLAP:

Introduction, Definitions, and Terminology, Characteristics of Data Warehouses, Data Modelling for Data Warehouses, Building a Data Warehouse, Typical Functionality of a Data Warehouse, Data Warehouse versus Views, Difficulties of Implementing Data Warehouses.

 

Course outcomes:

At the end of the course the student will be able to:

  • Select the appropriate high performance database like parallel and distributed database
  • Infer and represent the real world data using object oriented database
  • Interpret rule set in the database to implement data warehousing of mining
  • Discover and design database for recent applications database for better interoperability

 

Question paper pattern:

The SEE question paper will be set for 100 marks and the marks scored will be proportionately reduced to 60.

  • The question paper will have ten full questions carrying equal marks.
  • Each full question is for 20 marks.
  • There will be two full questions (with a maximum of four sub questions) from each module.
  • Each full question will have sub question covering all the topics under a module.
  • The students will have to answer five full questions, selecting one full question from each module.

 

Textbook/ Textbooks

1 Fundamentals of Database Systems Elmasri and Navathe Pearson Education 2013

2 Database Management Systems Raghu Ramakrishnan and Johannes Gehrke McGraw-Hill 3rd Edition, 2013.

 

Reference Books

1 Database System Concepts Abraham Silberschatz, Henry F. Korth, S. Sudarshan McGraw Hill 6th Edition, 2010