>I agree, and I've come to the conclusion that you should avoid designing a database schema until you have some clear understanding about how the application you're persisting data for will be used.<
I don't buy this argument, with due respect. (I see a lot of this thought these days and I'm genuinely worried we are about to swing the pendulum of software design into the dark ages where focus from the data model is taken away in favour of convenience of process design, front end design and data access frameworks).
In my experience: the objects from the problem domain will always have certain immutable relationships with each other right from the beginning. You have to look for them first before you do anything. They are clearly identifiable. What to persist and what not to persist are also discernible from existing manual business processes and the documents operational staff use daily (many of these are legal documents like tax invoices, contract confirmation, mandates and policy agreements etc ... a great way to start is to look at what reports users might need. Yes, those boring reports! Start there). Then, cardinalities and ordinalities will be known the moment you understand the objects relationships too (Can a client with product A also have product B? etc). Then, identifiers, business keys and other coding formats are also determined very early on in the project.
All of this before you even choose a front-end framework or the people's favourite ORM library.
I start with the data model. I use a good ER modeling tool to avoid frustrating myself when large changes are needed for my model. The models, when sufficiently complete, are printed in large format and pasted on walls for all to see daily. That is then considered holiest of holies.
(I understand that data models that need changes other than adding new columns or new sub entities can be painful to refactor ... but the fear of this eventuality should not automatically translate into turning the development process on its head.)
Too often we confuse analysis with design, then the heartaches start. Some problem domain things are immutable, some are not, some change over a fixed range, some are firm but expected to change, etc. All that stuff is critical to know as part of analysis.
I'd argue that you can do analysis incrementally right along with everything else. Reports sound like a great starting point. I agree with your advice, even the part about the pendulum swinging too far the other way. The problem is that, honestly, we suck no matter which way the pendulum swings. We continue to confuse the process with the goals.
>All that stuff is critical to know as part of analysis.
Exactly. I wonder if the frustration to get started as soon as possible ultimately results in data models that aren't ready yet and therefore brittle (IOW: insufficient analysis and logical testing of the data models before UI and other process logic commenced).
I think the fear from defining the models too early is that you won’t see what’s not needed, this approach probably has a tendency towards adding unnecessary models, indices, etc.
I don't buy this argument, with due respect. (I see a lot of this thought these days and I'm genuinely worried we are about to swing the pendulum of software design into the dark ages where focus from the data model is taken away in favour of convenience of process design, front end design and data access frameworks).
In my experience: the objects from the problem domain will always have certain immutable relationships with each other right from the beginning. You have to look for them first before you do anything. They are clearly identifiable. What to persist and what not to persist are also discernible from existing manual business processes and the documents operational staff use daily (many of these are legal documents like tax invoices, contract confirmation, mandates and policy agreements etc ... a great way to start is to look at what reports users might need. Yes, those boring reports! Start there). Then, cardinalities and ordinalities will be known the moment you understand the objects relationships too (Can a client with product A also have product B? etc). Then, identifiers, business keys and other coding formats are also determined very early on in the project.
All of this before you even choose a front-end framework or the people's favourite ORM library.
I start with the data model. I use a good ER modeling tool to avoid frustrating myself when large changes are needed for my model. The models, when sufficiently complete, are printed in large format and pasted on walls for all to see daily. That is then considered holiest of holies.
(I understand that data models that need changes other than adding new columns or new sub entities can be painful to refactor ... but the fear of this eventuality should not automatically translate into turning the development process on its head.)
Just my 2c.