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DATA WAREHOUSING AND DATA MINING [1]

Paper Code: 
MIT 421B
Credits: 
6
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: 
2015-16 [2]

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Source URL: https://www.csit.iisuniv.ac.in/courses/subjects/data-warehousing-and-data-mining-10

Links:
[1] https://www.csit.iisuniv.ac.in/courses/subjects/data-warehousing-and-data-mining-10
[2] https://www.csit.iisuniv.ac.in/academic-year/2015-16