IndianTechnoEra: Data Warehousing Syllabus | IndianTechnoEra

Data Warehousing Syllabus | IndianTechnoEra

 B. Tech. (5th Sem) 

(Computer Science & Engineering)

BCSE-541 (Data Warehousing and Data Mining)

Course Objectives:

• 1.To acquire the knowledge about Data Warehousing.
• 2.To learn about Data Mining concepts.
• 3.To learn about various Data Mining techniques.
• 4.To acquire knowledge about mining complex data objects.

Unit-1:Data Warehousing

Definition, usage and trends, DBMS Vs Data warehouse, data marts, metadata, Multidimensional data mode, data cubes, Schemas for Multidimensional database: stars, snowflakes and fact constellations, Data warehouse process & architecture, OLTP Vs OLAP, ROLAP Vs MOLAP, types of OLAP, servers, 3-Tier data warehouse architecture, Distributed and virtual data warehouses, data warehouse manager.

Unit-2: Data Mining

Definition & task, KDD versus Data mining, Data mining techniques, Tools and applications, Data mining query languages, Data specification, specifying knowledge, Hierarchy specification, pattern presentation & visualization specification.

Unit-3: Data Mining Techniques

Association rules, Clustering techniques, Decision tree knowledge discovery through Neural Networks & Generic Algorithm, Rough Sets, Support Victor Machines and Fuzzy techniques.

Unit-4: Mining Complex Data Objects

Spatial databases, Multimedia databases, Time series and sequence data, mining text Databases and mining World Wide Web.

Course Outcomes:

• 1.Understand operational database, warehousing and multidimensional need of data base to meet industrial needs.
• 2.Identify and understand the components of warehousing.
• 3.Identify and understand the data extraction and transformation techniques.
• 4.Identify and understand the Business analysis, query tools and application, OLAP etc.
• 5.Introduce with and gain knowledge about data mining, decision tree, neural networks and clustering.

Text/Reference Books:

• 1.Sam Anahory & Dennis Murray, “Data warehousing in Real World”, Pearson.
• 2.Jiawei Han & Micheline Kamber, Morgan Kaufmann, “Data Mining-Concepts & Techniques”.
• 3.Arun Pujar, “Data Mining Techniques”, University Press, Hyderabad.
• 4.Pieter Adriaans & Dolf Zantinge, “Data Mining”, Pearson Education.
• 5.Alex Berson, “Data Warehousing, Data Mining and OLAP”, McGraw Hill.
• 6.Mallach, “Data Warehousing System”, McGraw Hill.
• 7.W.H. Longhman, C.Klelly, “Building the Data Warehouses”, John Wiley & Sons.
• 8.W.H. Longhman, C.Klelly, “Developing the Data Warehouses”, John Wiley & Sons.
• 9.W.H. Longhman, C.Klelly, “Managing the Data Warehouses”, John Wiley & Sons.

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