Data Cleaning (or Data Scrubbing) is a process of detecting and correcting corrupt or inaccurate records by which any errors from a record or database are fully investigated and corrected to ensure that data outputs are as accurate as possible before final results are produced. Common inaccuracies in data include missing values, misplaced entries, and typographical errors. The Data Cleaning techniques are: 1) Remove duplicate or irrelevant observations; 2) Fix structural errors; 3) Remove unwanted outliers; 4) Add or modify missing data; 5) Validate.
Related Definitions in the Project: The Project Management; Project Administration; Document Review and Approval
