DATA WAREHOUSING AND DATA MINING

Paper Code: 
MIT 421B
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, 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: 

Implementation of Data warehouse, Physical design: steps, considerations, physical storage, indexing.

9.00
Unit V: 

Basics of data mining, related concepts, Data mining techniques, Data Mining Applications.

ESSENTIAL READINGS: 

1. Paulraj Ponnian, .”Data Warehousing Fundamentals”, John Wiley.

REFERENCES: 
  1. Jiawei Hen and Micheline Kamber, “ Data Mining Concepts and Techniques”
  2. Sima Yazdani, Shirley S. Wong, “Data warehousing with oracle “
  3. Han Kamber, Morgan Kaufmann, “Data Mining Concepts and Techniques“
  4. “Introduction to Business Intelligence and Data Warehousing”, PHI
  5. Ralph Kimball, “The Data Warehouse Lifecycle tool kit”, John Wiley.
Academic Year: 
2019-20
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