(this article was originally published in 2011 – I’ve made a few minor amendments today, nothing to change the message)
Time spent using colours, font styles etc. can definitely increase both the clarity and usefulness of a model. If that use of colours and styles can be automated, even better. Previously, I’ve used macros in a data modelling tool to define styles for entity symbols that depend on the business owner, and font styles that vary according to when the data (master data in this case) is expected to be available. I also colour-coded relationships to denote the business area responsible for managing them, which is not always obvious. This information was all held as properties on the entity and relationship, making the macro pretty straight forward.
You can also use colours and styles to highlight entities or tables affected by a given release or change request; again, this is possibly metadata that is available for a macro to query.
One great use of colour-coding and styles is to categorise entities on a diagram, using colours to denote the owning subject area.
I recently examined a data model where all the entities were categorised into a number of subject areas, and there was a separate ERD for each subject area. Unfortunately, the model suffered from a complete lack of artwork. There was no colour coding, so I couldn’t tell which subject area any of the entities belonged to (though of course I could guess some of them), so I couldn’t be sure which ERD I needed to look at to see the full context of a given entity. I had to use the main model ERD to be sure that I was seeing the full picture for an entity; this showed all the attributes for every entity, and made no use of styles or colour whatsoever; it was a difficult diagram to work with. Thankfully, it did fit onto a single sheet of A3 paper, as the model was quite small. In this data model, the subject areas were virtually unusable and irrelevant, because they weren’t being communicated at all.
When creating subject areas, think carefully about why you need them, and how users of the model should interpret them. You could break the model down into data-related subject areas, functional areas, system of record, etc. With a really large model, you may be able to justify having multiple sets of subject areas for different purposes.
Take the example of subject areas based upon a higher-level data model; let’s say that the higher-level model includes 60 concepts, including:
‘Abstract Geography’ includes 15 entities, including ‘Company Location’, ‘Country’, and ‘City’. ‘Exploration’ includes 20 entities, including ‘Well’ and ‘Field’. Both ‘Well and ‘Field’ will have relationships to entities within ‘Abstract Geography’. Here’s part of the complete LDM:
Note that the colours tell you which subject area ‘owns’ each entity, and also which subject area is responsible for populating relationships. The diagrams were created in SAP PowerDesigner, which uses the triangle symbol on the relationship line to indicate a dependent entity. here’s the same diagram in Idera ER/Studio Data Architect
Assume I have separate subject area ERDs for my concepts; where can I be sure of seeing all the relationships between the ‘Abstract Geography’ and ‘Exploration’ entities? I would expect to see all of them on BOTH subject area ERDs. It would even be possible to code a macro that tells you which entities should be on a given subject area ERD; again based on the metadata in the model.
Is any of this art? No, but it is a combination of graphic design, common sense, and ergonomics, with a tasty dash of automation to make it more palatable.