Data Mining
Last Updated: July 29, 2026 | By Mihail Sebastian | AI Dictionary
The process of discovering patterns, relationships, and anomalies in large datasets – the 1990s term for much of what is now called data science.
What is Data Mining?
Data mining is the process of discovering patterns, relationships, and anomalies in large datasets using statistical and machine learning techniques.
The term dominated the field in the 1990s, when it emerged from database research under the banner of “knowledge discovery in databases.” Much of what data mining named then is called data science now; the older term survives mainly for the pattern-discovery step itself.
Types of Data Mining Techniques
The techniques split into two camps. Some search for structure in unlabeled data; others learn from labeled examples and apply what they learned to new records.
- Association rule learning finds items that occur together, the method behind market basket analysis.
- Clustering groups similar records without predefined labels, the basis of customer segmentation.
- Classification assigns records to known categories, as in fraud flags and medical diagnoses.
- Anomaly detection surfaces records that fit no pattern, which is where fraud and equipment faults show up first.
Example of Data Mining
Market basket analysis at a supermarket chain. The chain mines millions of till receipts, and association rule learning scores every pair of products by how much more they sell together than apart.
The output drives concrete decisions: high-scoring pairs move to nearby shelves or into bundled promotions. The chain re-runs the mining each season, because the pairings shift with weather, holidays, and fashion.
No hypothesis went in; the patterns came out of the receipts. That direction of travel, from data to hypothesis rather than the reverse, is the defining trait of data mining.
Related AI terms: Data Science · Clustering · Anomaly Detection · Exploratory Data Analysis · Big Data
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Mihail Sebastian — Writes about AI governance, regulation, and the technology behind them. Placeholder bio — replace with a real credential line. About