Unit-1
Data warehousing-Introduction,definition,multidimensional data model, OLAP operations,schema,architecture,data marts,meta data,OLAP Engine, backend process.
Data mining-definitions,KDD,DM Techniques,problems,issues and challenges, applications.
Association rules-Introduction,methods,Apriori,partition,pincer search algorithm, dynamic item set counting,FP-Tree growth algorithms, incremental algorithm

Unit-2
Clustering techniques-Introduction, partitioning algorithm, hierarchical algorithms,
Categorical clustering
Decision trees-Introduction, tree construction principle, Best split, construction algorithms, construction with presorting

Unit-3
Nueral networks, genetic algorithm
Web mining-content mining, structure mining, usage mining, text mining, text clustering
Temporal data mining-Introduction, Temporal association rules, Sequence mining,GSP,
SPADE, Episode discovery, event prediction, Time series, Spatial mining.

Unit-4
Data ware house applications-Grocery store,warehouse,shipments,value chain, and their Combination, Financial services, Subscription business,Insurance,voyage business

Unit-5
Factless fact tables, building a dimensional data ware house,Aggregates,Back room operations, Front Room operations, Front End applications, Future trends

Suggested reading:
Arun K Pujari-Data miningTechniques,universities press,2001
Ralph Kimball-The data ware house Tool kit, John Wiley1996

References:
Jake sturm-Data Warehousing with SQL server 7.0 Technical Reference,PHI2000
Michael J A Berry, Gordon S Linoff,Mastering data mining,Wiley2001