Data Mining Vs Data Warehousing

Data Mining	Data Warehousing
Data mining refers to the process of extracting useful data from the databases.	Data Warehouse refers to a place where data can be stored for useful mining.
Data mining is primarily used to discover and indicate relationships among the data sets. Data mining tools utilize AI, statistics, databases, and machine learning systems to discover the relationship between the data. Data mining tools can support business-related questions that traditionally time-consuming to resolve any issue.	Data warehouse refers to the process of compiling and organizing data into one common database advanced requests can be made against the warehouse storage of data.
Process of determining data patterns.	A database system designed for analytics.
The process of extracting useful data from a large set of data.	The process of combining all the relevant data.
Features of Data Mining	Features of Data Warehousing
Business entrepreneurs carry data mining with the help of engineers.	Data warehousing is entirely carried out by the engineers.
Data is analyzed repeatedly.	Data is stored periodically.
Data mining uses pattern recognition techniques to identify patterns.	Data warehousing is the process of extracting and storing data that allow easier reporting.
One of the most amazing data mining techniques is the detection and identification of the unwanted errors that occur in the system.	One of the advantages of the data warehouse is its ability to update frequently.
The data mining techniques are cost-efficient as compared to other statistical data applications.	The responsibility of the data warehouse is to simplify every type of business data.
Advantages of Data Mining	Advantages of Data Warehousing