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PAPER VII: DATA MINING AND WAREHOUSING Subject Description: This Paper presents introduction to Data mining, Classification, Clustering and data warehousing. Goals: To enable the students to understand the concept of data mining and techniques of data mining. Objectives: On successful completion of the student should have:  Understood the concept of data mining.  Learnt Classification, Clustering and Data warehousing. Content:

Unit I
Basic data mining tasks – data mining versus knowledge discovery in data bases- data mining issues – data mining metrices – social implications of data mining – data mining from a database perspective. Data mining techniques: Introduction – a statistical perspective on data mining – similarity measures – decision trees – neural networks – genetic algorithms.

Unit II
Classification: Introduction – Statistical based algorithms – Distance based algorithms – decision tree based algorithms – neural network based algorithms – rule based algorithms – combining techniques.

Unit III
Clustering: Introduction – Similarity and distance measures – Outliers – Hierarchical Algorithms – Partitional Algorithms. Association rules: Introduction – large item sets –basic algorithms – parallel and distributed algorithms – comparing approaches – incremental rules – advanced association rules techniques – measuring the quality of rules.

Unit IV
Data warehousing: An Introduction – characteristics of a data warehouse – data marts – other aspects of data mart. Online analytical processing: Introduction – OLTP & OLAP systems – data modeling – star schema for multidimensional view – data modeling – multifact star schema or snow flake schema – OLAP TOOLS – State of the market – OLAP TOOLS and the inernet.

Unit V
Developing a data WAREHOUSE: why and how to build a data warehouse – data warehouse architectural strategies and organization issues – design consideration – data content – meta data distribution of data – tools for data warehousing – performance considerations – crucial decisions in designing a data warehouse. Applications of data warehouse and data mining in government: Introduction – national data warehouses- other areas for data warehousing and data mining.

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