How data modelling has been in the enterprises

Well, it all depends...

For an enterprise where modelling is considered as an important step towards the maturity of IT development, process, functionality, and data modelling (and others like user experience) are an important part of developers' life.

What's interesting to see is that data modelling has not been considered as so important compared to functionality or process parts in most organizations. It is not difficult to understand this. The E-R modelling discipline has served most transnational system designs and other tricks, such as multidimensional modelling has been well used in most situations before. And I believe many S-M or close to L size organizations still have no problem of only doing some basic E/R modelling and hire good DBAs to take care of the rest for the next decades.

The difference is that some, I cannot find a better word than some, organizations do have good business in the past and have acquired different lines of business and owned different systems for many years. When they do the integration of IT solutions (they will end-up doing this most of the time), it has been extremely difficult to integrate on the process, or functionality. or any other levels. Data model is the only possible easy way to let the integration succeed. So, it is just the recent years that many large or X large organizations started to realize the importance of controlling their data, meaning the data modelling, data quality, master data, and meta-data.

Another angle is to look at the vendors of data modelling tools and data models. There have been quite a lot of data modelling tools (we mentioned this in a previous note) in the market but there are only a few leaders in the market, most of whom also provide large database engines. And vendors of data models are extremely limited to giant software vendors. So this market up-to-now has been very limited.

This phenomenon looks interesting and even funny to me. Most of people talk about information explosion in the new IT era. But it is also these people who choose not to understand their data, which is then translated to information for some purposes. :)