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

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

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

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

 
9.00

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

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: