Glossary

Data scrubbing is the process of cleaning raw datasets by identifying and correcting errors, removing duplicates, and resolving inconsistencies. It ensures that analyses are built on accurate, reliable data—leading to more trustworthy insights, improved model performance, and better strategic decisions.