juniorData Mining
What is data preprocessing in data mining?
Updated May 15, 2026
Short answer
It is the process of cleaning and preparing raw data for mining.
Deep explanation
Preprocessing includes handling missing values, removing duplicates, normalization, encoding categorical variables, and noise reduction. It improves data quality and directly impacts model performance.
Real-world example
Cleaning customer databases before building churn prediction models.
Common mistakes
- Ignoring missing values or assuming models handle them automatically.
Follow-up questions
- What is data imputation?
- Why is normalization needed?