What is Data Cleaning?

Data cleaning is the process of identifying, correcting, or removing inaccurate, incomplete, or irrelevant data from a dataset to improve its quality and reliability. It involves tasks such as removing duplicates, handling missing values, correcting errors, standardizing formats, and validating data against predefined rules.

Effective data cleaning is essential for accurate analysis and decision-making. By ensuring that data is consistent, complete, and accurate, businesses can enhance the quality of insights derived from analytics, improve predictive models, and boost overall efficiency in data-driven processes. Clean data is a foundation for making reliable, informed business decisions.