Let’s imagine that we are a few years down the road and that data mesh has had some reasonable success stories and a few notable failures chalked down to its name.
Imagine a new data fad arrives on the scene. Let’s call it Info Messiah.
Imagine that the Info Messiah folk want to move into the spaces occupied by data mesh. What do they do? Easy. Rubbish data mesh and claim it can’t do this, that or the other thing. It can’t scale, it’s too bureaucratic. Too fragmented. Too monolithic. Too anarchical. Too obtuse. Too blah, blah, blah.
The data mesh folk complain because the Info Messiah folk are singling out “data mesh in name” only, and pretending that it applies to all manifestations of data mesh. Successes, mediocre results or failures.
So, the data mesh folk say that the Info Messiah folk are being unreasonable and that data mesh is a valid paradigm, and that the Info Messiah folk should retract their erroneous, misinformed and unhelpful claims.
To which the Info Messiah folk come back with “we were only criticizing centralized data mesh, what’s the issue?”
Back to Kansas
Here’s a couple of questions to ponder:
Why don’t data mesh folk make it clear what they mean when they refer to centralized data warehousing?
Do they actually mean centralized data warehousing or the centralized provisioning and development of the infrastructure to support data warehousing as a corporate process and function, just like sales and marketing, finance, or legal?
As a result of applying data mesh will end up with the mother and father of all shadow data app landscapes. A tessellation of decentralized, autonomous, and disjointed pieces in federated anarchy?
Did any of the data mesh folk actually read my blog piece, Myth-busting: Data Mesh and Data Warehousing https://goodstrat.com/2021/11/25/myth-busting-data-mesh-and-data-warehousing/ from start to finish?
That’s it folks
As I have said before, it is like the fake news of data; irritating, time-wasting, and unnecessary. I do however hope that the data mesh folk rectify their view of data warehousing.
Many thanks for reading.
The Big Data Contrarian and author of Laughing @ Big Data.