It works well, but has many issues too. User’s SQLs and input data can differ, often in unpredictable ways, because they bring their own and expect the central team to handle the rest. Those edge cases break the standardization rules, fails the workflow, confuses the user because the platform is a black box, and they ask about changing it or adding a new feature. Now your standardization asks are bottle-necked by this central team, and the options are:
- to wait for the central team to fix/improve it
- find some hack around the platform
- don’t use the platform and its associated toolings, so you build it yourself and have another disjoint system for a specific use case
- central team might build a feature that one team asked for 1 years ago, but now nobody needs it anymore and nobody knows why it’s in code. Repeat many many times for various asks over the years and your code base is likely a foreign mess.
- give your resources/funding to the central team to prioritize your ask. When built and a few years later, the central team owns something they themselves never wanted.
>>data vault 2.0 brings with it methodology, architecture, modeling, and implementation – best practices, standards, automation and more. the ability to encompass and leverage disciplined agile delivery, and sei/cmmi, six sigma, lean initiatives, cycle time reduction, and proper build practices lead us to one day sprint cycles.
And let's not forget that shit show of a "book" https://www.amazon.com/Data-Architecture-Primer-Scientist-Wa...