Monday morning, 9am: three hours of manual work
The client's team started every week the same way — logging into multiple supplier portals, downloading reports one by one, reformatting data from different formats into a single spreadsheet, and timestamping everything before it could be used. Three hours of work that produced no analysis, no insight, just clean data to start from.
The work was necessary. Every minute of it was mechanical. And it happened every single week.
The pipeline we built
We built a Go-based automation that runs on a schedule and handles the entire sequence without anyone touching it:
- Scheduled ingestion. Connects to each data source at configurable intervals — no manual trigger needed.
- Format normalization. Each source has different column names, date formats, and encoding. The pipeline normalizes everything into one clean schema before storage.
- Deduplication and versioning. Reports that overlap in date range are deduplicated. Historical versions are retained for audit.
- Timestamped output. Structured, dated files ready for the business workflow — exactly the format the team was previously creating by hand.
What changed
The three-hour Monday process became zero hours. The data arrives structured, timestamped, and ready before anyone logs in. The team that used to do the gathering now does the analysis.
No dashboards. No visualizations. No AI. Just reliable, automatic data delivery — which turned out to be the only thing that actually needed solving.