What is the difference between data mining and data warehousing?

Answer 1

Data mining is the process of finding patterns in a given data set. These patterns can often provide meaningful and insightful data to whoever is interested in that data. Data mining is used today in a wide variety of contexts – in fraud detection, as an aid in marketing campaigns, and even supermarkets use it to study their consumers.

Data warehousing can be said to be the process of centralizing or aggregating data from multiple sources into one common repository.

Answer 2

The primary differences between data mining and data warehousing are the system designs, methodology used, and the purpose. Data mining is the use of pattern recognition logic to identity trends within a sample data set and extrapolate this information against the larger data pool. Data warehousing is the process of extracting and storing data to allow easier reporting.