I will clean and validate your excel or CSV data with review flags
Google Sheets Apps Script Automation Specialist
Informazioni su questo servizio
Messy spreadsheets can slow down reporting, migration, and customer data cleanup.
I clean and validate Excel, CSV, and CRM export files against agreed rules, standardize clear values, and flag uncertain or conflicting records for review.
What I can check:
- Formatting, dates, phone numbers, statuses, and company names
- Likely duplicates
- Missing, invalid, conflicting, or suspicious values
- Data that does not match your rules or reference file
What you receive:
- A separate cleaned and validated output
- Standardized values where the source is clear
- REVIEW and CRITICAL_REVIEW flags
- An Issues / Exception Log
- A short validation summary
Your original file stays unchanged.
This is a file-based service. I do not access live CRM systems, use APIs, or import data automatically.
Contact me first for large, sensitive, multi-table files or complex rules.
FAQ
What files can I send?
You can send CSV files, Excel spreadsheets, or file-based CRM exports. Please anonymize unnecessary sensitive data before sending.
Do you need access to my CRM?
No. Send only the export file required for cleanup. The work is done on a separate copy, not inside your live system.
Will you automatically fix every issue in my file?
No. I only correct values when the source or rule is clear. Uncertain, conflicting, or risky cases are flagged for review instead of being guessed.
Will you change my original file?
No. Your original file stays unchanged. I provide a separate cleaned output, a review file for uncertain rows, and a brief cleanup summary.
Can you remove duplicate contacts?
Yes. I can identify likely duplicates using fields such as email, phone number, name, and company. Uncertain matches are flagged for your review instead of being removed automatically.
Can you validate my data against my own rules or source file?
Yes. If you provide clear rules, reference files, or expected formats, I can compare the data against them, flag mismatches, and separate uncertain cases for review.

