I think you're getting the idea -- both your points kinda highlight that this is something that companies want, but are not really getting.
As for the market, various sources have the "enterprise software market", whatever that means, at somewhere around $100 billion to $300 billion. We also see companies trying over and over to do this kind of thing. The demand is clearly there.
Certainly the mandate "help run the business" is a wide concern, and that's an OK working definition of "enterprise", and what most existing solutions are trying to do. There are hundreds of interconnected concerns, lots of things to coordinate, etc.
There are other wide concerns, though. Almost anything in engineering and science. Take, for example, the question "how can we reduce our greenhouse gas emissions?" which a lot of companies are asking (or being forced to ask). If you wanted to build a SAAS product for helping companies reduce their GHG, you've got a wide problem, because there are a thousand activities that can emit GHG, and any given company is going to be doing dozens of them at once. But each company is different. Each state and country thinks of things differently. You might not even have the same calculations state-to-state.
Hard problems in science and engineering are just naturally cross-disciplinary, meaning your system has to know a lot of things about a lot of subjects. There are just thousands of little complicating differences and factors. If you're trying to solve a problem like this, absolutely do not de-normalize your database.
As for the market, various sources have the "enterprise software market", whatever that means, at somewhere around $100 billion to $300 billion. We also see companies trying over and over to do this kind of thing. The demand is clearly there.
Certainly the mandate "help run the business" is a wide concern, and that's an OK working definition of "enterprise", and what most existing solutions are trying to do. There are hundreds of interconnected concerns, lots of things to coordinate, etc.
There are other wide concerns, though. Almost anything in engineering and science. Take, for example, the question "how can we reduce our greenhouse gas emissions?" which a lot of companies are asking (or being forced to ask). If you wanted to build a SAAS product for helping companies reduce their GHG, you've got a wide problem, because there are a thousand activities that can emit GHG, and any given company is going to be doing dozens of them at once. But each company is different. Each state and country thinks of things differently. You might not even have the same calculations state-to-state.
Hard problems in science and engineering are just naturally cross-disciplinary, meaning your system has to know a lot of things about a lot of subjects. There are just thousands of little complicating differences and factors. If you're trying to solve a problem like this, absolutely do not de-normalize your database.