Data mining is the process of discovering hidden, valid, and actionable patterns and knowledge from massive sets of data.
The Knowledge Discovery Process Steps
According to the diagram, the complete process flows through the following stages:
- Databases and Flat Files: The raw source data stored in various formats.
- Cleaning and Integration: Removing noise, handling missing data, and combining multiple data sources.
- Data Warehouse: The centralized repository where clean, integrated data is stored.
- Selection and Transformation: Choosing relevant data for the analysis task and transforming it into useful formats.
- Data Mining: The core step where intelligent, algorithmic methods are applied to extract data patterns.
- Evaluation and Presentation: Interpreting the discovered patterns and presenting them visually (e.g., charts or reports) to the user.
- Knowledge: The final usable insight gained from the entire process.
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