Definition
Data Cleaning is the process of identifying and resolving errors, inconsistencies, duplicates and missing values to improve Data Quality.
Human Explanation
Data are corrected so that they are complete, consistent and reliable before analysis begins.
Why it Matters
Errors in data lead to incorrect analyses and flawed decisions.
Conceptual Boundary
Data Cleaning should not change the meaning represented by the data. Its purpose is to improve the quality of existing data.
Practical Perspective
The best results come from cleaning data systematically during Data Collection and Data Integration rather than waiting until analysis begins.