A commodity price database that updates itself.
Commodity Database Automation
Before
2 analysts, daily
Now
Zero manual hours
The challenge
An energy trading firm's commodity price database was kept current by two analysts updating it by hand every single day.
What we built
An automated ingestion and enrichment pipeline. ZEMA pulls price data on schedule, Python handles calculations and validation, and the database stays current with no human input.
How it runs
- PullZEMA ingests price data automatically
- EnrichPython runs calculations and validation
- ServeDatabase always current, no manual input
The result
- 0
- Manual hours per day
- 2
- Analysts redeployed
- 99.8%
- Data accuracy
Built with
- ZEMA
- Python
- Database automation
Run this in Energy & Renewables
The same Data & databases build, scoped to your sources and your reporting lines.