Data Mining

The practice of analyzing large databases in order to generate new information.

How it works

Data mining applies statistical and machine learning techniques to large datasets to discover previously unknown patterns and relationships. A typical pipeline involves data cleaning to handle missing or inconsistent values, feature engineering to extract relevant signals, and the application of algorithms such as association rule mining (finding items that co-occur), clustering (finding natural groups), classification (predicting categories), and regression (predicting continuous values).

Why it matters

Data mining transformed the value of enterprise databases from passive records into active sources of competitive insight. Retail companies use it for market basket analysis and personalisation. Insurers use it for fraud detection. Healthcare providers mine patient records for treatment patterns. In the AI era, data mining practices for cleaning and curating training datasets are directly critical to the quality of the models built on top of them.