Status: Delivered. Described from our own delivery records. Client identity, brand and commercial terms are withheld. Figures, where given, cover the period stated and nothing beyond it.
Context
A healthcare operation receiving weekly insurance data files covering coverage and claims for hospital patients.
Before hospital personnel could act on any of it, someone had to load the files, clean and transform them, run the analysis and produce the charts.
The problem
- Every weekly cycle repeated the same manual extraction and transformation work.
- The delay between the data arriving and the data being usable ate into the week it described.
- Manual handling introduced variation, so week-to-week comparisons were not always sound.
- Hospital staff had no direct access — they received output, and had to ask for anything else.
What we built
An automated weekly ingestion and transformation pipeline
Triggered on arrival rather than run by hand.
An analytics processing stage
Producing the measures consistently every cycle.
A web portal with multiple dashboard tabs
For hospital personnel, so the output is somewhere they can go rather than something they wait to receive.
How we delivered it
- 1
Document the manual process
Exactly as performed, including the judgement calls, before automating any of it.
- 2
Automate ingestion
With validation on arrival and alerting on missing or malformed files.
- 3
Automate transformation and analysis
With the same measures every cycle.
- 4
Publish
To the portal, with the tab structure driven by what staff actually needed to see.
- 5
Run in parallel
For several cycles, comparing automated output against the manual result before switching over.
How it was phased
Indicative phasing for work of this shape. Actual duration varies with data quality, access and decision speed.
What the client keeps
- Pipeline code in their own repository
- The transformation logic documented
- Validation rules
- The portal and its source
- The parallel-run comparison record