For the last couple of years, I have written about various ways to work with Microsoft Fabric Real-Time Intelligence data, both about ingesting, enriching, and representing real-time data.

Adding Microsoft Fabric RTI to any IoT solution will add instant value because it’s another ‘head’ on top of IoT platforms, and it’s so easy to integrate.

It adds both Remote monitoring and Predictive maintenance capabilities based on real-time information flows, using telemetry and context data coming from IoT platforms and related enterprise systems. This is the easiest way to get real-time insights on an enterprise level.

Combining that real-time telemetry with slow-moving context data can be hard, though.

In the past, I used Azure Digital Twins together with Azure Data Explorer to cope with this challenge. A timeseries database shows us the historical time-series data in tables as ‘silos’. The digital twin environment gives us the modelled situation, the here and now, plus relationships. These two datastores complement each other.

Using Fabric Graph, we have learned how to model entities and relationships as nodes and edges. What if we could add real-time data to this?

Entering Fabric Ontology.

Let’s check out Fabric Ontology and see what is offered in this new Digital Twin experience within Microsoft Fabric.

Doorgaan met het lezen van “First look at Fabric Ontology”