Part 4: Data Manipulation in Data Cleaning
Towards AI
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Machine Learning
Robotics
Data Science
AI Research
How Small Fixes Permanently Shape What the Data Is Allowed to Say There is an assumption many teams carry without fully examining it. It feels corrective. It feels like a necessary step to improve data quality before analysis or machine learning begins. But data cleaning is not neutral. Every cleaning decision alters the structure, distribution, and meaning of the dataset. When rows are removed, values are replaced, missing fields are filled, or outliers are excluded, the dataset is no longer a raw representation of reality. It becomes a curated version of it.