Data cleaning

Processing a dataset to make it easier to consume. This may involve fixing inconsistencies and errors, removing non-machine-readable elements such as formatting, using standard labels for row and column headings, ensuring that numbers, dates, and other quantities are represented appropriately, conversion to a suitable file format, reconciliation of labels with another dataset being used (see data integration), etc. See data quality.