Data warehousing & data mining: Difference between data mining and data warehousing.

Explain the difference between data mining and data warehousing.

Data warehousing is merely extracting data from different sources, cleaning the data and storing it in the warehouse. Where as data mining aims to examine or explore the data using queries. These queries can be fired on the data warehouse. Explore the data in data mining helps in reporting, planning strategies, finding meaningful patterns etc.

For example: A data warehouse of a company stores all the relevant information of projects and employees. Using Data mining, one can use this data to generate different reports like profits generated etc.

Explain the difference between data mining and data warehousing.

Data mining is a method for comparing large amounts of data for the purpose of finding patterns. Data mining is normally used for models and forecasting. Data mining is the process of correlations, patterns by shifting through large data repositories using pattern recognition techniques.

Data warehousing is the central repository for the data of several business systems in an enterprise. Data from various resources extracted and organized in the data warehouse selectively for analysis and accessibility.

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