EnergyPredictive Analytics
From high costs to near real-time insights with Zerobus Ingest
Beusa Energy
Beusa Energy, a 30-year energy sector company spanning electric hydraulic fracturing, mobile power generation, electrical distribution, field gas processing and industrial manufacturing, migrated its high-frequency telemetry ingestion from a custom SQL Statement API pipeline to Databricks' Zerobus Ingest direct-write API. The migration required only swapping the write path (same .NET worker, same MQTT subscriptions), cutting ingestion cost from roughly 689 DBU per GB to about 0.29 DBU per GB, a 99% cost reduction, while eliminating the need for a separate streaming broker tier. Today more than 6,000 devices stream telemetry at 1 Hz across about 250 remote assets, ingesting ~22 million rows daily into a unified lakehouse with end-to-end latency of about three seconds, governed by Unity Catalog. Beusa is now using this high-frequency telemetry, combined with maintenance history, to train predictive-maintenance models forecasting remaining useful life of assets, moving from condition-based to predictive and eventually prescriptive maintenance.
