A data platform for an energy lab
The problem
The lab's instruments stream readings non-stop, and the previous MariaDB setup had reached its limits: millions of rows, slow reports, and no warning when a device stopped sending or started sending zeros. Missing data is the failure nobody notices — nothing looks broken.
What I am building
- TimescaleDB on new hardware, with readings sent straight from the instruments.
- New devices and measurements added by configuration, not by rewriting code.
- Faster reporting in Power BI and on the lab's website, from summaries the database keeps up to date in the background.
- A watchdog in Python on every stream: gaps are logged; zero and impossible readings are flagged.
- Anomaly detection with machine learning on the installations' power output.
- EV-charging price forecasting from charging-station data.
- A technical manual, so the lab can run and extend the platform on its own.
Aim
Reports that read ready-made summaries instead of millions of raw rows, and a platform the lab can grow without code. Load times will be measured before and after, as on the energy hub.
Relevant if your role mentions
Data engineeringTime series databasesMonitoring and alerts PythonMachine learningForecastingData streaming in faster than your reports can keep up? Two lines are enough to start.
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