A pharma market in one database: products, pharmacies, prices and reviews.
German pharmaceutical company.
- 6
- independent data pipelines
- Hundreds
- of pharmacies and their offers
- Tens of thousands
- of historical price records
- Data pipelines
- Analytics database
Illustrative images created with AI. The projects and their results are real.
The challenge
Market data was spread across several industry sources, in different formats. Gathering it by hand was slow, and by the time it was compiled it was already out of date.
What we built
A data platform with one pipeline per domain that pulls products, pharmacies, variants, reviews and prices from structured sources into one central database.
What it does
- Thousands of products with their attributes
- Pharmacy coverage and pharmacy-specific prices
- Price changes stored over time, never overwritten
- Product reviews and ratings
- Incremental updates during the week and a full weekly refresh
- Every pipeline run logged for monitoring
The result
The business team analyses prices, positioning, pharmacy coverage and customer sentiment on current data, with the full price history behind it.
New sources plug in as modules without touching the core.
How we built it
Python pipelines on REST and JSON interfaces, a relational SQLite database and scheduled runs.
Our role
Concept, architecture and development, with clear IP and usage rights for the client.
Technology
- 6 scheduled pipelines
- Python
- REST APIs
- SQLite