Query Optimization using SQL Approach for Data Mining Analysis

Relational databases are acceptable repository for structured data; integrating data mining algorithms with a relational DBMS is an essential research issue for database programmers. In a relational database, a significant effort is required to prepare a summary data set that can be used as input for the data mining process. It requires many complex SQL queries, joining tables and aggregating columns. This paper realizes the research on extending SQL code for data mining processing and related work on query optimization. Also the paper proposes the following approaches, transposition, pivoting and cross tabulation. The approaches exhibit efficient optimizations with SQL extensions using aggregated Queries.

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