Why this chapter matters
Dirty data causes wrong groupings, broken joins, and misleading KPIs.
What you will learn
- Normalize text casing, whitespace, and hidden characters.
- Convert mixed-format dates and numeric text into true date and number values.
- Flag duplicates, blanks, and invalid categories with repeatable checks.
Lessons in this chapter
- Text normalizationUse TRIM, CLEAN, and case functions to standardize labels.
- Type correctionTurn text-like numbers and dates into real typed values. Read the full guide →
- Duplicate controlIdentify and handle repeated records safely.
- Validation rulesApply data validation to prevent future input errors.
Study task
Clean a customer list with inconsistent city names and date formats, then report the corrections you applied.
Chapter checkpoint
Why can two date values that look the same still fail to match in a lookup?
One may be text while the other is a true date serial number, so Excel treats them as different values.