The postit approach is a no-brain way to give functional meaning to the TSDB. It is functional simple and fast. Though it may not free from technically setting up the requesting environment (such as ElasticSearch engine).
The drawback being the lack of readability impairing the business commitment to the Information System functional coherence.
The conclusion is that the postit approach is suitable for IT-only driven initiatives, with little cost and no special organisation.
When it comes to address Hypervision ambitions, the functional contextualization data on top of the whole TSDB becomes first-class in the enterprise.
The data composing the functional contextualization goes beyond the IT domain.
Definitely, this information is the property of the whole enterprise. And as such, it must be constructed by the IT with full business commitment.
The state-of-the-art of constructing enterprise-class information is to use the Entities-Attributes-Relationships UML tools to communicate and deliver the data.
As such, IngeniBridge software is fully data-model-centric.
In its data offer, Deagital promotes the data modeling as the first step in this initiative.
Our first example is open public on GitHub. Click here to access the UML Data Model. It can also be viewed just down.
Before describing the contents of this UML Data Model, we must keep in mind the goal to functionally describe the time series stored in our TSDB database.
So the modeling of all the entities and their attributes is set to support the functional contextualization of the time series in the TSDB.
The model is visible down: