September 3, 2025

Dealing with Dirty Data: How Alice Helps Normalize the Mess

Dirty data is inevitable. Whether you’re working with Access, FoxPro, CSVs, or exports from homegrown systems. For operations and BI teams, cleaning this manually is painful, repetitive, and error-prone. That’s where Alice steps in.

Dirty data is inevitable. Whether you’re working with Access, FoxPro, CSVs, or exports from homegrown systems, the mess will find you:

Missing fields
Placeholder values
Misaligned headers
Mixed data types

For operations and BI teams, cleaning this manually is painful, repetitive, and error-prone. That’s where Alice steps in.

Common Dirty Data Edge Cases

1. Placeholder Nulls
Legacy exports often use N/A, 9999, or - to represent missing data.
Alice maps these automatically to true nulls.

2. Mixed Data Types
One column might contain numbers, text, and blanks — breaking aggregations.
Alice enforces consistent typing (numeric, datetime, text).

Keep reading this blog on alice.dev

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