What Data Mining Meaning, Applications & Example
The process of discovering patterns and insights in large data sets.
What is Data Mining?
Data Mining is the process of discovering patterns, trends, and insights from large datasets using statistical and computational techniques. It involves extracting useful information from data, which can be applied in decision-making and predictive analytics.
Types of Data Mining Techniques
- Association Rule Learning: Identifies relationships between variables, commonly used in market basket analysis.
- Clustering : Groups similar data points, useful for customer segmentation and anomaly detection .
- Classification : Sorts data into predefined categories, often applied in fraud detection and medical diagnosis.
Applications of Data Mining
- Marketing: Helps businesses analyze customer behavior and personalize marketing strategies.
- Healthcare: Identifies patterns in patient data for disease prediction and treatment optimization .
- Finance: Detects fraudulent transactions and evaluates credit risk.
Example of Data Mining
An example of Data Mining is retail sales analysis, where transaction data is mined to find purchasing patterns, enabling retailers to optimize inventory, plan promotions, and improve customer satisfaction.