Pretty gentle learning path to understanding data mesh: https://datameshlearning.com/intro-to-data-mesh/

I appreciate it!

This is "solved" (at least to some degree) by adding additional resources to the domain teams - data engineers get embedded and/or added to domain teams to become the data product developers in most implementations. Hard agree that you cannot give a team significantly more responsibilities without more resources to help handle them.

Is this done in an incremental way? Changing the org from the central-data-team-as-bottleneck to this is a huge step. Just thinking of all the buy-in you need makes me dizzy. Everyone seems to want direct access to the data, but are they willing to do the effort of taking responsibility for it as well?

I'd love to see how a smooth transition to this goes :)

I’d worry that the extra headcount will just get sucked into operational priorities.

The payroll engineers are always going to prioritise fixing payroll problems over supplying data scientists. More engineers could easily just end up being used fixing the backlog.

Feel free to throw in the data mesh community Slack[1]. There was an interesting approach that sounds kinda similar re schema contract management from FindHotel that they posted a few weeks ago re data mesh[2].

1 https://launchpass.com/data-mesh-learning 2 https://blog.findhotel.net/2021/07/the-evolution-of-findhote...

That's kind of one of the reasons for data mesh. The domain is the one who controls how the data is stored and made available so they get to show off how useful their data is and might get some great insights back. But if the team is so lacking in empathy, that data mesh implementation will almost certainly fail. So there needs to be at least some buy-in but if you can convince a domain that participating is a public good (which many do) and that they actually have more control like this (they get data engineers added or at least embedded in their team), it can be gravy/groovy.

Seems like data mesh assumes a culture of good will and acting in good faith,

I help run the data mesh community and yup, 100%. There's a reason data mesh is catching on as fast as it is because, if done right, it really feels like it can solve a lot of the agility/scalability problems people feel re data/analytics now. It is NOT a silver bullet but it can potentially really help companies towards that (obnoxiously named and overused) goal of being data driven.