If you discover that you missed a column, then you would have to rerun the whole thing. For example, you run it in erwin, then export it out to Excel, and then you have to do a lot of cosmetic modification. That's better than it was, but it's still a little cumbersome. I think it was version 8 where you had to use Crystal Reports, and it was so painful that the company I was with just stayed on version 7 until version 9 came out and they restored the data browser. The report generation has room for improvement. If you're just going in and making changes to a handful of tables, I didn't find the reporting capabilities that flexible or easy to use. That was quicker than trying to run reports out of erwin, because sometimes we got mixed results which took us more time than what they were worth. We could also share the information on team calls, then everybody could see it. However, sometimes I would find it quicker to just do a screenshot of the tables in the data model, put it in a Word document, and send it to the software designers and business users to let them see that this is how I organized the data. When you do a data model, you can detect the table.
Apart from that, the solution seems to be fine. We will have to see what the scalability is like in that version. But when we go over to the server, the data models can automatically pull and push. When you have the desktop version, merging the models, two into one, requires more time. The version we're not using now-the server version-would definitely help us with the pain point when it comes to merging the models. So we are looking at the version that will be a server-based model, where the data modelers can bring the data out, they can share, and they can merge their data models with existing data model on the server. It becomes a nightmare for the senior data modeler to bring them together, especially when it comes to recreating them when you want to merge them. It has become a pain point to merge the models from individual desktops and get them into a single data model, when multiple data modelers are working on a particular project.
We are planning to move, in 2021, into their server version, where multiple data modelers can work at the same time and share their models.
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