EA Model Quality Management

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The challenge of maintaining model quality and consistency grows exponentially as our models and modelling teams grow. This presentation offers an approach to find and fix problems, and help your team model right the first time.

This webinar demonstrates how Model Expert helps to

- understand what is in your model
- understand how you can fix it, and
- understand how you can stop it from going wrong in the future.

Assumptions:

That the models, to be interesting, contain all kinds of different stuff – probably multiple projects. Including data modelling, process modelling, architecture, requirements management and more.
The people doing the modelling will be at different levels. Some will be very advanced and very clever, some would be just getting started.
We all know that

- the more people use EA, the more information goes in there;
- the more information in the model, the more useful the model;
- the more useful the model, the more people want to use it.
So, it’s a virtuous circle.

We need standards.

We need to be flexible, we need to be fast-moving and be able to change how we do things quite quickly. But we also need to provide more help to our modelers. Not just saying “here’s a quick linker”, “here’s a set of things in a toolbox”. It’s more coaching them, encouraging them.

This is where Model Expert originally came from.

1. Discovering what is in the model.
Everybody should know what exactly is in their model. What’s the structure of it? What types and stereotypes? Connectors? Diagram types? What fields in EA are you using? What tag values are you using? Everybody should know that. Sometimes we call that the metamodel.

2. Finding out what the matter is and fixing it.
Use the built-in tools to easily navigate to problem areas and fix them.

3. Guided modelling
How do we stop new EA teams from making the same mistakes again? Provide guidance to them exactly where and when they need it, and stopping them from doing the wrong thing.
Category
Management
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