The problem
Monthly exports arrive with different headers, inconsistent dates, duplicate rows, and values that need checking by hand. The work is slow, easy to get wrong, and difficult to repeat consistently.
Common examples
- Combine monthly CSV exports into one normalized dataset.
- Reconcile two spreadsheets and flag records that do not match.
- Remove duplicates, validate emails and dates, and produce a rejected-records report.
- Turn a manual weekly reporting process into one repeatable command.
- Convert inconsistent Excel workbooks into a clean import file for another system.
What you receive
- A working script or spreadsheet workflow you can run again.
- A merged, normalized output file in the format you need.
- A validation report showing rejected or unmatched records.
- A short handover explaining inputs, assumptions, and how to rerun it.
What I need from you
- One or two representative input files with sensitive values removed if possible.
- A description of the current manual process and the desired output.
- The rules for duplicates, required fields, and acceptable values.
- Any volume or frequency expectations.
Scope and limits
- I do not guess business rules that are not documented.
- Source files still need to be supplied in a usable format.
- Very large datasets may need a database or batch-processing approach.
How it works
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01
Assess
We start with the process, sample inputs, and the outcome you need. I confirm whether the work is a good fit before quoting.
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02
Agree on scope
We agree on the deliverable, assumptions, limitations, and how changes will be handled.
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03
Build
I build the smallest reliable solution that solves the problem, with clear checkpoints rather than a long silent stretch.
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04
Test
The solution is checked against representative samples, including edge cases and rejected records.
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05
Deliver
You receive the working files, a short handover, and clear next steps for running or maintaining the solution.
Relevant work
CSV Cleanup Utility
A Python command-line tool that turns messy CSV exports into clean, consistent data and a summary report.