Data mining is a data analysis process that companies and business owners use to examine raw data, including sales numbers, prices and customers, to develop better marketing strategies, improve performance or decrease the costs of running the business. Data mining also serves to discover new patterns of behavior among consumers.
Once a company analyzes the relevant data through database management utilities such as SQL Server from Microsoft or Data Mining Suite from Oracle, it applies the resulting information as a way to predict future factors related to the business. For example, grocery store and supermarkets use data mining techniques to analyze information regarding which consumers buy which products, how much they spend on those products and when they’re most likely to spend. Then, they use the information derived from the process to determine when to offer discounts and how to target products to certain consumers based on their buying habits. Coaches of some basketball teams, such as the Toronto Raptors, use data mining to devise a specific approach when facing different teams.
As of 2015, the two most common algorithms that companies use to analyze data include regression and classification. The former develops a mathematical formula based on the existing data, allowing companies to apply that formula to a new dataset to effectively predict future behavior, but it’s only useful for continuous data, including weight, time or speed. The latter is better suited for categorical data, including colors, names or gender.