The successful management of measurement data can be extremely challenging for many energy companies.

Do you feel like you are compromising the way you handle large volumes of measurement data? You shouldn’t have to regularly archive your data or even store it in a separate area. 

Perhaps you’re tired of having to set up rules for individual meters in an attempt to identify issues. These rules provide range and bound checks, and comparisons with  average trends and so on. While this seems like a plausible approach, it is time-consuming, error-prone, and ultimately unmaintainable for any but the simplest of assets. Customers report frequent false positives that are then silenced for periods, while actual meter problems go unrecognised.  

Traditional solutions tend to be inflexible, expensive and uncompromising. Many have primitive mechanisms for data validation, require laborious routes for issue identification and are limited in their ability to successfully handle large data volumes. In short, they cause problems rather than fix them.  

It’s time for a modern approach to managing your measurement data. 

Cloud technology is revolutionising the way energy companies manage their measurement data.

From machine learning anomaly detection to real-time data ingestion and processing, find out how solutions, like the EnergySys Measurement Service, are redefining the way measurement data is managed.