Pip: Good Strategy Rebellion — where the sacred cows of enterprise tech get a proper going-over. Today we’re deep in the data wars, asking whether the industry’s favourite architectural revolution is actually a revolution, or just the same old chaos in a new lanyard.

Mara: Martyn Jones has been writing about exactly that — covering the case against Data Mesh, what it means for how organisations actually govern and use their data, and why the rational data warehouse keeps refusing to stay dead.

Pip: Let’s start with the bonfire.

The case against Data Mesh

Mara: The question this segment is really asking is whether Data Mesh represents genuine architectural progress, or whether it’s the latest in a long line of industry fashions that repackage old problems and sell them as solutions.

Pip: The anchor here is a book review of F*CK DATA MESH, written in the voice of Paula Prada Price for the New College Tech Review. She sets the frame early: “Data Mesh isn’t innovation; it’s intellectual laziness masquerading as revolution.”

Mara: And the consequence of that framing is fairly stark. If the diagnosis is right, then billions of pounds currently flowing into decentralised data platforms are funding a rediscovery of problems that data professionals already solved — integration, governance, lineage, quality — without the institutional memory of how they were solved before.

Pip: The Brexit of data. That’s the book’s own analogy — grand promises of sovereignty and freedom from centralised oppression, followed by the discovery that decentralisation mostly means more silos, latency nightmares, and duplicated effort. It’s a barb that lands because the structural parallel is uncomfortably tidy.

Mara: A second review, “Why Data Mesh is Not the Future of Data Management,” picks up the same thread from a C-suite angle. It highlights what the book calls a “Bullshit Detection Kit” — a framework for identifying the bandwagon-chasers and buzzword dribblers who thrive on stack complexity. The Data Lakehouse gets labelled a “naive, dishonest, and disruptive fraud.” SAFe Agile is described as disastrous in complex enterprise transformations. The rush toward what the book calls “Degenerative AI” is framed as organisations preparing themselves for a technology they don’t understand.

Pip: That’s a fairly comprehensive sweep of fashionable nonsense in one volume.

Mara: The third review, from Alicia Altmann in the Middle Digital Review, pulls back to the broader cultural diagnosis. She notes that the book’s real target isn’t the technology itself but the performative culture around it — buzzwords as props, strategic announcements as substitutes for practical progress. Her line is precise: “The terminology evolves at a pace that would impress marketing departments but exhaust engineers.”

Pip: And all three reviews converge on the same unfashionable prescription: patient work, coherent governance, subject-oriented design, systems that serve people rather than justify consulting days.

Mara: The rational data warehouse, in other words. Not glamorous. Apparently, it works.

Pip: Which raises the question of what “actually working” looks like when organisations finally stop chasing the next stack — and that’s the territory worth sitting with.

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Mara: The throughline across all of this is a single uncomfortable question: how much of what the industry calls progress is actually just rebranded forgetting?

Pip: Patient, unglamorous, coherent — not a great conference keynote, but possibly a functioning data strategy. We’ll be back with more from Good Strategy Rebellion.