data mining versus knowledge discovery in databases , data mining issues, data mining metrics, 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.

Introduction, Statistical based algorithms, distance based algorithms, decision tree based algorithms, neural network based algorithms, rule based algorithms, combining techniques.

Introduction – Similarity and Distance Measures – Outliers – Hierarchical Algorithms - partition Algorithms. Association rules: Introduction - large item sets - basic algorithms – parallel &distributed algorithms – comparing approaches- incremental rules – advanced association rules techniques – measuring the quality of rules.

Introduction - characteristics of a data warehouse – data marts – other aspects of data mart. Online analytical processing: introduction - OLTP & OLAP systems – data modelling –star schema for multidimensional view –data modeling – multifactor star schema or snow flake schema – OLAP TOOLS – State of the market – OLAP TOOLS and the internet.

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