Advanced Concepts in Database Systems

Paper Code: 
CSC 144B
Credits: 
04
Periods/week: 
03
Max. Marks: 
100.00
Objective: 

This course will enable students:

  • To provide a deeper understanding of Query Processing and Optimization.
  • To introduce the fundamental techniques of various types of databases.
  • To provide understanding of Data warehousing and Data mining concepts.
  • To prepare students for advanced database concepts.

 

Course Outcomes: 

 

Topics

Teaching Hours

I

Query Processing, Optimization & Database Tuning:

Translating SQL Queries into Relational Algebra, Algorithms for External Sorting, SELECT and JOIN Operation, PROJECT and Set Operations. Pipelining, Using Heuristics in Query Optimization, Cost Estimations, Physical Database Design in Relational Databases, Database Tuning in Relational Systems, Database Tuning in Relational Systems

 

12

II

Distributed Database System: Types of Distributed Database Systems, Distributed Database Architecture, Data Fragmentation, Replication, Allocation Techniques, Query Processing, Transaction Management, Concurrency Control and Recovery, Distributed Catalog Management.

 

12

III

Object and Object-Relational Databases: Object Database Concetps, Object-Relational Features, ODMG Object Model and the Object Definition, Object Database Conceptual Design, The Object Query Language.

Enhanced Data Model for Advanced Applications: Introduction to Temporal Database Concepts, Spatial and Multimedia Databases, Active Database Concepts and Triggers, Introduction to Deductive Databases,

 

12

IV

Data Warehouse: Basic Concepts, Data Cube and OLAP, Design and Usage.

Data Mining: Kinds of Data, Kinds of Patterns, Technologies, Applications, Knowledge discovery, Major issues in Mining, Data Preprocessing.

Data Mining Tools and Techniques: Association rules, Clustering techniques, Classification and Prediction Techniques, Introduction to Data Mining Tools.

 

12

V

NoSQL Database and Big Data Storage Systems: The CAP Theorem, Document-Based, Key-value stores, Column-based, Graph Databases.

Big Data Technologies Based on MapReduce and Hadoop: Introduction to MapReduce, Hadoop, HDFS, Yarn.

Blockchain Database: Blockchain Properties, Consensus, Data Management in a Blockchain, Smart Contracts, Performance Enhancement, Emerging Applications.

 

12

 

REFERENCES: 

Books recommended:

  1. Elmasri, Navathe,” Fundamentals of Database Systems”, Addison Wesley, 7th Edition.
  2. Korth, Silbertz, Sudarshan,” Database Concepts”, McGraw Hill, 7th Edition.
  3. Han, Jiawei, Micheline Kamber, and Jian Pei, “Data mining: Concepts and. Techniques”, Morgan Kaufmann Publishers, 3rd Edition .
  4. Majumdar & Bhattacharya,” Database Management System”, TMH, 2nd Edition.
  5. Data C J,” An Introduction to Database System”, Addison Wesley, 8th Edition.
  6. Ramakrishnan, Gehrke,” Database Management System”, McGraw Hill, 3rd Edition.
  7. Peter Rob, Carlos Coronel,” Database systems: design, implementation, and management”, Thomson Learning, 9th Edition.
  8. Bernstein, Hadzilacous, Goodman,” Concurrency Control & Recovery”, Addison Wesley.

 

Academic Year: 
2025-26
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