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ETL Testing - Interview Questions
What is the Difference between Data Warehouse and Data Mining?
Data Warehousing Data Mining
It involves gathering all relevant data for analytics in one place.  Data is extracted from large datasets using this method. 
Data extraction and storage assist in facilitating easier reporting.  It identifies patterns by using pattern recognition techniques. 
Engineers are solely responsible for data warehousing, and data is periodically stored.  Data mining is carried out by business users in conjunction with engineers, and data is analyzed regularly. 
In addition to making data mining easier and more convenient, it helps sort and upload important data to databases.   Analyzing information and data is made easier. 
It is possible to accumulate a large amount of irrelevant and unnecessary data. Loss and erasure of data can also be problematic.  Not doing it correctly can create data breaches and hacking since data mining isn't always 100% accurate. 
Data mining cannot take place without this process, since it compiles and organizes data into a common database.  Because the process requires compiled data, it always takes place after data warehousing.  
Data warehouses simplify every type of business data.  Comparatively, data mining techniques are inexpensive. 
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