What Is a Data Audit?

A data audit is a systematic review of your data to find and fix quality issues.

Common Data Quality Issues

1. Missing Values

• Empty cells where data should exist
• Can cause formula errors (#N/A, #REF!)
• Solution: Fill with 0, "Unknown", or research the correct value

2. Invalid Values

• Negative quantities (can't have -10 items)
• Out-of-range numbers (age of 200)
• Wrong data types (text in a number column)
• Solution: Correct to valid values

3. Outliers

• Values that are unusually high or low
• $1,250 unit price when others are $2-$90
• May be errors or may be legitimate (investigate!)

4. Duplicates

• Same record appears multiple times
• Solution: Remove duplicates (you learned this!)

The Audit Process

• Check for blanks: Use COUNTBLANK() or filter for empty cells
• Check ranges: Use MIN/MAX to find extreme values
• Check types: Look for text in number columns
• Check duplicates: Use COUNTIF to find repeated values
• Document findings: Note what you found and how you fixed it

In the Lab

You'll audit an inventory dataset and fix the quality issues you find!