This guest post is written by Jay Funnell, Chief Solution Architect, Honeywell Process Solutions
No, this isn't the opening line to a rude joke but a true story. It happened while en route to a client site near Brisbane where we were hosting a product demonstration. There was the usual ebb and flow of traffic when a peculiar car drove past.
The Canadian said, "Look it's a Ranchero". The Australian said, "That's a Ute". And the Venezuelan chimed in, "No, no, El Camino!"
We grew up in different surroundings yet had a shared understanding of the vehicle that looked part car, part truck. We shared our individual experiences with this vehicle with three different names and did so without much formality.
It seems counter-intuitive to first identify all possible aspects of a thing before speaking of it, yet this is exactly what traditional modeling tools ask of us.
Traditional relational models have a great deal of flexibility…up until they are put into production. Once data lands in a table and reports are built, it becomes difficult to change the existing tables and entity relationships.
Semantic models, on the other hand, are more suited for supporting an ‘ecosystem’ of data, especially in an environment where change is the norm:
This fresh approach supports the Microsoft Upstream Reference Architecture (MURA), an IT architecture that serves as a common, reliable environment for the implementation and integration of the many technologies that make up the modern digital plant. Ultimately, this architecture will help to dramatically improve efficiency and cost-effectiveness for upstream oil and gas analysis, operations, and business.
Discover the outcome of the Ranchero/Ute/El Camino conversation, and learn more about the benefits of semantic data modeling in your digital plant.