Distributed Databases

Paper Code: 
MIT 421C
Credits: 
06
Periods/week: 
12
Max. Marks: 
100.00
Objective: 

The purpose of this course is to focus on the design and implementation of data warehousing, data marts, and provide necessary knowledge of data.

9.00
Unit I: 

Need for strategic information, Decision support system, Challenges in DM ,Operational versus Decision-Support Systems, Data Warehousing-the only solution, definitions of Data warehousing and data mining, features of Data warehouse, Data Marts, Metadata.

9.00
Unit II: 

Trends in Data Warehousing: significant trends and growth.
Planning Data warehouse, project team, project management considerations, information packages & requirements gathering methods and Requirements definition: Scope and Content.

9.00
Unit III: 

Architectural components: Objectives, Data Warehouse Architecture, Distinguishing Characteristics, Architectural Framework. Infrastructure: Operational & Physical.

9.00
Unit IV: 

Basics of data mining, related concepts, Data mining techniques, Data Mining Applications.
Data mining: Introduction, Learning, Neural Networks, Data mining using neural networks, Genetic algorithms.

9.00
Unit V: 

Web Mining: Web mining, Text mining, Content mining, Web structure mining. Searching Techniques: Optimal, non-optimal, Min-max, H –I pruning.

ESSENTIAL READINGS: 

1. M. Tamer Ozsu, Patrick Valduriez, “Distributed Database System”, PHI.

REFERENCES: 

1. Ceri and Pelagatti, “Distributed Database Principles and Systems”, McGraw Hill.

Academic Year: 
2018-19
  • Printer-friendly version