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← All selected workReporting that runs while the business moves.
A production reporting workflow designed around scale, validation and less manual repetition.
Outcome348 stores · 30 countries · 11 checks
Evidence levelUnverifiedScale or method documented; quantitative impact, adoption or net savings still need confirmation.
StackPython · SQL · ETL · data quality
01 / Context
The question behind the work.
Worldwide sell-out reporting combined recurring files, multiple markets and a high cost of manual checks. A useful output had to be reliable before it reached the business.
02 / Built
Structure before decoration.
Built production pipelines that ingest, validate and prepare recurring reporting inputs, with automatic data quality checks and a human review step before delivery.
03 / Result
What changed.
The README estimates approximately 30 minutes of manual processing per run. Actual run frequency, end-to-end runtime, review time and net monthly savings have not been verified.
This case study is intentionally anonymised. It describes the shape, scale and outcome of the work without exposing internal data, client systems or confidential screenshots.
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