Data Mining – Definition

Cite this article as:"Data Mining – Definition," in The Business Professor, updated July 30, 2019, last accessed October 27, 2020,


Data Mining Definition

Data mining is a method used by companies to generate new and useful information from existing raw data. When a company searches through existing databases, analyzes patterns of the raw data to get useful information, this is data mining.

There are certain techniques that a company can adopt when it comes to data mining. For instance, a business can use software to search and analyze patterns of an existing raw data or database. The main objective of data mining is to find correlations within large raw data in order to come up with better strategies in running the affairs of the company.

A Little More on What is Data Mining

The basics of data mining is effective and accurate data collection and a reliable computing processing through the use of computer software. Data mining involves that asssempbake of large number of pre-existing data in a company, analysing the data and organizing them to discover new and useful trends.

The new patterns or information extracted from the existing database can be used for risk management, better advertising and marketing and other processes that makes a company perform better. There are five steps in a data mining process, they are;

  • Assemble the data, organize them and put them in a data warehouse.
  • Store and manage the data collected.
  • Sort out the data into different categories using software application.
  • Extract or collect new and useful information from the data.
  • Present them in a table or graph for use.

Data Warehousing and Mining Software

Data mining processes are used based on the type of information to be extracted and the nature of the data to be organized, analyzed and sorted. There are different requests of users or companies when it comes to accessing new information from pre-existing data. Generally, professionals that extract new and useful information from pre-existing raw data is known as a data miner.

A data miner is responsible for organizing, analysing and sorting out pre-exiting data to get new information useful for the improvemnet of the organization or business. The importance of warehousing in data mininng cannot be overemphasized. When a company’s data are centralized in a database, this is warehousing. It is more like a storage system.

Data Mining Example

Many businesses use data mining, supermarkets and grocery stores are examples of businesses that use data mining processes. A supermarket that offers loyalty cards to customers can easily track trends in sales and demands using the cards. What customers purchase at a particular time and the price for the product purchased is stored and used as data for making business decisions. Selected data that inform the decisions of the management of a business but cover all sample groups so that it can be effective.

Here is a summary of what you should know about data mining;

  • Data mining is a process of extracting new and useful information from the existing raw data.
  • It entails analyzing a large batch of pre-existing information to discover new patterns that can be employed in a business to achieve fantastic result.
  • Warehousing is an essential aspect of data mining.
  • Data mining is used by businesses to develop effective marketing strategies, increase sales and minimize costs and losses.
  • Data mining programs entail analyzing and sorting out business trends in relation to the information provided or requested by users.

Reference for “Data Mining”

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