[Term of the Day]: Data Mining

Term of the Day

“Data Mining”

Definition — What is Data Mining and its purpose?

Data Mining, also known as Knowledge Discovery in Data (KDD), is a process of digging through and analyzing enormous sets of data and then extracting the meaningful patterns and trends.

In general, “Mining” is the process of extraction of some valuable material from the earth e.g. coal mining, diamond mining and so on. In the context of computer science, “Data Mining” refers to the extraction of useful information from a bulk of data or data warehouses.

This helps to predict behaviors and future trends, allowing businesses to make proactive, knowledge-driven decisions. For businesses, data mining is used to discover patterns and relationships in the data in order to help make better business decisions.

A simple example of Data Mining:

Grocery stores are well-known users of data mining techniques. Many supermarkets offer free loyalty cards to customers that give them access to reduced prices not available to non-members. The cards make it easy for stores to track who is buying what, when they are buying it and at what price.

After analyzing the data, stores can then use this data to offer customers coupons targeted to their buying habits and decide when to put items on sale or when to sell them at full price.

The insights derived via Data Mining can be used for various purposes. Specific uses include:

Market segmentation - Identify the common characteristics of customers who buy the same products from your company.
Customer churn - Predict which customers are likely to leave your company and go to a competitor.
Fraud detection - Identify which transactions are most likely to be fraudulent.
Direct marketing - Identify which prospects should be included in a mailing list to obtain the highest response rate.
Interactive marketing - Predict what each individual accessing a Web site is most likely interested in seeing.
Market basket analysis - Understand what products or services are commonly purchased together.
Trend analysis - Reveal the difference between a typical customer this month and last.