Data mining

Data mining is the computational process of analyzing datasets to discover patterns, relationships, or other useful information. It combines statistical, machine-learning, and database methods to extract patterns that can support decisions or further investigation.

Association rule learning: A data-mining method that finds items or events that frequently occur together in datasets. It exposes co-occurrence patterns, such as products commonly bought in the same transaction.
Database: An organized collection of data stored and accessed electronically. Data mining commonly draws on records held in structured databases.
Market basket analysis: The analysis of transaction records to find products that customers purchase together. It applies association rules to retail purchasing data.
Exploratory data analysis: The use of visual and statistical summaries to investigate a dataset before formal modeling. It overlaps with mining but emphasizes open-ended examination and human-guided summaries.
Classification: A supervised learning task that assigns records to predefined categories using labeled examples. It uses discovered patterns to assign new records to known classes.
Statistics: The discipline of collecting, analyzing, interpreting, and presenting data. Statistical reasoning underlies estimates of whether discovered patterns are meaningful.
Customer segmentation: The division of customers into groups with shared characteristics or behaviors. Clusters and other patterns can guide targeted services and marketing.
Data warehousing: The collection and organization of data from multiple sources for reporting and analysis. Warehousing prepares and stores data; mining searches it for previously unknown patterns.
Clustering: A method that groups data points by similarity without requiring predefined labels. It reveals structure when useful categories are not already known.
Machine learning: The study of algorithms that improve performance on tasks through experience with data. Many mining workflows use learning algorithms to detect or predict patterns.

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