CSVTU BE VIII Semester IT Data Mining & Warehousing Syllabus


Semester:VIII Branch: Information Technology.

Subject:Data Mining & Warehousing

Unit-I Overview and Concepts:

Need for data warehousing, Basic elements of data warehousing, Trends in data warehousing. Planning

And Requirements: Project planning and management, Collecting the requirements. Architecture And

Infrastructure: Architectural components, Infrastructure and metadata.

Unit-II Data Design and Data Representation:

Principles of dimensional modeling, Dimensional modeling advanced topics, data extraction, transformation

and loading, data quality.

Unit-III Information Access and Delivery:

Matching information to classes of users, OLAP in data warehouse, Data warehousing and the web.

Implementation And Maintenance: Physical design process, data warehouse deployment, growth and


Unit-IV Data Mining Introduction:

Basics of data mining, related concepts, Data mining techniques Data Mining Algorithms: Classification,

Clustering, Association rules. Knowledge Discovery: KDD Process.

Unit-V Web Mining:

Content Mining, Web Structure Mining, Web Usage mining. Advanced Topics: Spatial mining, Temporal

mining. Visualisation : Data generalization and summarization-based characterization, Analytical

characterization: analysis of attribute relevance, Mining class comparisons: Discriminating between

different classes, Mining descriptive statistical measures in large databasesData Mining Primitives,

Languages, and System Architectures: Data mining primitives, Query language, Designing GUI based on a

data mining query language, Architectures of data mining systems Application and Trends in Data Mining:

Applications, Systems products and research prototypes, Additional themes in data mining, Trends in data


Text Books:

Prabhu,Data ware housing- concepts, Techniques, Products and Applications, Prentice hall of India

Soman K P, “Insight into Data Mining: Theory & Pratice” , Prentice hall of India

M.H. Dunham, “Data Mining Introductory and Advanced Topics”, Pearson Education.

Reference Books:

Paulraj Ponniah, “Data Warehousing Fundamentals”, John Wiley.

Gupta, “Introduction To Datamining with Case Studies”, PHI

Ralph Kimball, “The Data Warehouse Lifecycle toolkit”, Joh

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