End-to-End Methodology for Mining from Datasets

Abstract

Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Data mining is widely used domain for extracting trends or patterns from historical data. Generally, data sets that are stored in a relational database or a data warehouse come from On-Line Transaction Processing (OLTP) systems in which database schemas are highly normalized. But data mining, statistical or machine learning algorithms generally require aggregated data in summarized form. Also many data mining algorithms require the result to be transformed into tabular format. Tabular datasets are the suitable input for many data mining approaches.