Difference Between Data Mining and Data Warehousing

In this post, we will understand the difference between data mining and data warehousing.

Data Mining

• It is a process used to determine data patterns.

• It can be understood as a general method to extract useful data from a set of data.

• Data is analysed repeatedly in this process.

• It is done by business entrepreneurs and engineers to extract meaningful data.

• It uses many techniques that includes pattern recognition to identify patterns in data.

• It helps detect unwanted errors that may occur in the system.

• It is cost-efficient in comparison to other statistical data processing techniques.

• It isn’t completely accurate since nothing is ideal in the real-world.

Data Warehousing

• It is a database system that has been designed to perform analytics.

• It combines all the relevant data into a single module.

• The process of data warehousing is done by engineers.

• Here, data is stored in a periodic manner.

• In this process, data is extracted and stored in a location for ease of reporting.

• It is updated at regular intervals of time.

• This is the reason why it is used in major companies, in order to stay up-to-date.

• It helps simplify every type of data for business.

• Data loss is possible if the data required for analysis is not integrated to the data warehouse.

• It stores large amounts of historical data that helps the user in analysing the trends and seasonality to make further predictions.