Don't just validate data types. Validate logical constraints. If a task's status is "Complete," its "Completion Date" must be present. If a value is "High Priority," its "Due Date" must be within 7 days. This flags deeper inconsistencies.
The "Feedback Loop to Source System Owners" Loop
When you encounter consistent patterns of messy input, don't just fix it and move on. Share specific examples with the owner of the source system or process. Often, a small change upstream (e.g., adding a dropdown in their form, changing an export setting) can eliminate hours of downstream work for everyone.
The "Micro-Automation Snippet Library"
Don't build one giant script. Build a library of small, reusable code snippets brother cell phone list (for Python, VBA, or even complex spreadsheet formulas) that handle specific micro-transformations (e.g., "Extract date from string," "Clean product ID," "Normalize status field"). Piece them together as needed.
The "Human-in-the-Loop AI Training" (Even for Spreadsheets)
Use your manual cleaning efforts to train your automated process. When you fix a specific parsing error, update your REGEX or IF statements. When you manually categorize a new item, add it to your lookup table. You're constantly improving your "AI" (your formulas/scripts).
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