Difference Between Data Mining and Database

Data mining

Data mining is the process of analyzing data from a different perspective and summarizing it into useful information – information that can be used to increase revenue cuts cost or both.

Data mining the analysis step of the knowledge discovery in database process. For example, data mining software can help retail companies find customers with a common interest.

The phrase data mining is commonly misused to describe software that presents data in new ways. True data mining software doesn’t just change the presentation, but actually discovers the previously unknown relationship among the data.


The database is a collection of interrelated data and a set of programs to access those data.

It is a software system that manages data stored in the database. It provides an effective method of defining, storing and retrieving the information contained in the database. (the primary goal of a DBMS is to provide an environment that is both convenient and efficient to use in retrieving and storing database information.

It provides users with information that they required. Some examples of DBMS packages are dBASE, FoxPro, FoxBase, Oracle, Ms-Access etc..

Read More: Difference Between Primitive and Non-Primitive Data Types

Database Data mining
The database is the organized collection of data. Most of the times, these raw data are stored in very large databases.

A Database may contain different levels of abstraction in its architecture.

Typically, the three levels: external, conceptual and internal make up the database architecture. 
Data mining is analyzing data from different information to discover useful knowledge.

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.

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