Branch : Information Technology, VIII Semester
Course: Data Mining and Warehousing
Unit II: Data Warehouse and OLAP technology, Multidimensional data models and different OLAP Operations, OLAP Server: ROLAP, MOLAP, Data Warehouse implementation ,Efficient Computation of Data Cubes, Processing of OLAP queries, Indexing data.
Unit III: Data Mining: Data Preprocessing ,Data Integration and Transformation, Data Reduction, Discretizaion and Concept Hierarchy Generation , Basics of data mining, Data mining techniques, KDP (Knowledge Discovery Process), Application and Challenges of Data Mining, Introduction of Web Structure Mining, Web Usage Mining, Spatial Mining, Text Mining, Security Issue, Privacy Issue, Ethical Issue.
Unit IV: Mining Association Rules in Large Databases: Association Rule Mining, Single-Dimensional Boolean Association Rules, Multi-Level Association Rule, Apriori Algorithm, Fp-Growth Algorithm, Time series mining association rules, latest trends in association rules mining.
Unit V: Classification and Clustering Distance Measures, Types of Clustering, K-Means Algorithm,Decision Tree Induction, Bayesian Classification, Association Rule Based, Other Classification Methods, Prediction, Classifier Accuracy, Categorization of methods, Partitioning methods, Outlier Analysis.
Data Mining and Warehousing Reference:-
P.Ponnian, “Data Warehousing Fundamentals”, John Weliey.
Han,Kamber, “Data Mining Concepts & Techniques”, M.Kaufman.
M.H.Dunham, “Data Mining Introductory & Advanced Topics”, Pearson Education.
Ralph Kimball, “The Data Warehouse Lifecycle Tool Kit”, John Wiley.
M.Berry , G.Linoff, “Master in Data Mining”, John Wiley.
W.H.Inmon, “Building the Data Ware houses”, Wiely Dreamtech.
E.G. Mallach , “The Decision Support & Data Warehouse Systems”, TMH