What is the Difference Between Data Mining and Data Warehousing

KEY DIFFERENCE Data mining is considered as a process of extracting data from large data sets, whereas a Data warehouse is the process of pooling all the relevant data together. Data mining is the process of analyzing unknown patterns of data, whereas a Data warehouse is a technique for collecting and managing data.

1. What is the difference between database and data mining?
2. What is the difference between data mining and OLAP?
3. How does the data mining and data warehousing work together?
4. Is data mining possible without a data warehouse?

What is the difference between database and data mining?

The database is the organized collection of data. ... Data mining deals with extracting useful and previously unknown information from raw data. The data mining process relies on the data compiled in the data warehousing phase in order to detect meaningful patterns.

What is the difference between data mining and OLAP?

OLAP and data mining are used to solve different kinds of analytical problems. OLAP summarizes data and makes forecasts. ... Data mining discovers hidden patterns in data and operates at a detailed level instead of a summary level.

How does the data mining and data warehousing work together?

How does the data mining and data warehousing work together? Data warehousing can be used for analyzing the business needs by storing data in a meaningful form. Using Data mining, one can forecast the business needs. Data warehouse can act as a source of this forecasting.

Is data mining possible without a data warehouse?

The straightforward answer is yes, data mining can be carried out without the presence of a distributed data warehouse.