Glossary · Data Analytics

What is Data Cleaning?

Fixing or removing incorrect, duplicate, inconsistent and missing data so analysis can be trusted.

In more detail

Typical steps: remove duplicates on a unique key, handle missing values, standardise categories, fix types and units, and check for impossible values — documenting every change.

Example

Mapping "Bangalore", "bengaluru " and "Bengaluru" to one value.

Learn it properlyData Cleaning for Beginners: Fix Missing Values, Duplicates and Messy Formats10 min lesson · Data Analytics

Related terms

Full glossary

DataFrame (pandas)A table of rows and columns in Python’s pandas library, used to clean, analyse and reshape data.KPI (Key Performance Indicator)A number that shows how well a business or team is doing against an important goal.Pivot TableA spreadsheet tool that summarises data — sums, counts, averages — grouped by categories, by dragging fields.SQL JOINA SQL operation that combines rows from two tables based on a related column.Window FunctionA SQL function that calculates across related rows without collapsing them into one row.