KDD Process of Data Mining

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Knowledge Discovery in Databases (KDD) is the process of discovering useful knowledge from the collection of data.

Here's a simple breakdown of its steps:

1. Data Selection: Choosing the relevant data from a larger dataset.
2. Data Preprocessing: Cleaning and preparing the data to ensure quality and consistency.
3. Data Transformation: Converting the data into a suitable format or structure for analysis.
4. Data Mining: Applying algorithms to extract patterns and insights from the data using clustering, classification, or association rule mining techniques to find trends.
5. Interpretation/Evaluation: Making sense of the mined data, evaluating the patterns, and turning them into useful knowledge.