Data Mining Techniques: Extracting Value from Raw Data

Data mining involves discovering patterns and insights from large datasets using AI and statistical techniques.

Common Data Mining Techniques

• Classification – Assigning labels to data (e.g., spam detection in emails).

• Clustering – Grouping similar data points (e.g., customer segmentation).

• Association Rule Mining – Finding relationships between data points (e.g., "customers who buy X often buy Y").

• Anomaly Detection – Identifying unusual patterns (e.g., fraud detection).

Applications of Data Mining

• Marketing – Customer behavior analysis.

• Healthcare – Predictive analytics for disease prevention.

• Finance – Risk management and fraud detection.

Data mining is a crucial tool for businesses aiming to transform raw data into actionable insights.