Data Mining Methodology

Data Mining:CRISP - Data mining

Data mining can be defined as the process of extracting valid, authentic, and actionable information from large databases using various data mining techniques like machine learning, artificial intelligence (AI) and statistics to derive patterns and trends that exist in data. These patterns and trends can be collected together and defined as a mining model.

Almost all industries these days are taking advantage of this technique including manufacturing, marketing, chemical, aerospace etc. to increase their business efficiency. Therefore the needs of a standard data mining process increased dramatically which should be easy, comprehensive, reliable and uniform across the industry.

Data Mining Methodology:-

As a result in 1990 a Cross Industry Standard Process for Data Mining (CRISP-DM) first published the uniform and standard process for data mining by defining below 7 steps

1. Defining the problem – Understanding Business Process Continue reading