Beware the Fake Data Mesh: Legacy Dressed Up as Progress
Enterprises have been promised "self-service" data platforms for years. The reality? Most of today's so-called modern solutions are nothing more than consulting-heavy models with a new coat of paint.
The False Promise of Self-Service
Enterprises have been promised "self-service" data platforms for years. The reality? Most of today's so-called modern solutions are nothing more than consulting-heavy models with a new coat of paint. They talk about democratization, but what they deliver is dependency.
Be warned:"If your 'self-service data mesh' depends on 12 engineers building APIs and data pipelines just so a business team can ask a question, you don't have a mesh, you have legacy dressed up as progress."
Why Fake Mesh Persists
This isn't an accident. Vendors and consultants thrive on keeping businesses dependent. Long transformation projects, endless pipeline builds, and complex governance frameworks guarantee revenue for them, but deliver little for the enterprise.
The results speak for themselves.
48%
Digital initiatives deliver business outcomes
Gartner reports that only 48% of digital initiatives deliver business outcomes.
85%
Big data projects never reach production
85% of big data projects never reach production.
These numbers don't signal innovation. They signal a system designed to stall.
The Real Intent of Data Mesh
The original idea behind Data Mesh was never about more pipelines or central control. It was about domains owning their data products, where the real business context lives.
But instead of enabling business teams, many "mesh" programs have been hijacked by data engineering. What should have been a business revolution has been turned into another IT project, complete with bottlenecks and consultants billing by the hour.
As BARC Germany's research highlights, most enterprises confuse Data Mesh with architectures and platforms. In truth, its value lies in business ownership, product thinking, and accountability at the domain level.
AI Changed the Game. Some Just Didn't Get the Memo.
The Old World
In the pre-AI world, engineers built data contracts, APIs, and layers of translation to compensate for their lack of business context. The Linux Foundation formalized this work into standards, and for a while, it made sense.
But that world is gone.
The New Reality
AI has erased the need for those brittle stopgaps. It can structure, contextualize, and make data usable, directly with the business.
McKinsey notes that AI-enabled data platforms reduce time-to-insight by up to 70%, while Forrester calls AI in data management the key enabler of scalability.
The message is clear: the bottlenecks of the past are not just inefficient, they're irrelevant.
How to Spot a Fake Mesh
Here's the test:
Can a business team create and share a data product without writing code?
Is governance embedded in the product, not buried in IT bureaucracy?
Are engineers focused on scaling and optimizing, or still hand-cranking every pipeline?
If the answer is "no," then you don't have a mesh. You have legacy dressed up as progress.
The Hidden Agenda
Why cling to this outdated model? Because it keeps control, and budgets, firmly in the hands of engineers and consultants. In an AI-enabled world, their relevance shrinks.
But clinging to control doesn't create value. It just delays it. Enterprises that insist on legacy practices will watch faster, leaner competitors overtake them.
Where Data Tiles Fits In
At Data Tiles, we built Latttice to put the business back in charge. Latttice uses AI to let domain teams access their data wherever it resides, create governed products in minutes, and connect seamlessly into visualization tools with zero code required.
01
Access data wherever it resides
Domain teams can reach their data without engineering bottlenecks
02
Create governed products in minutes
Build data products with embedded governance, not IT bureaucracy
03
Connect seamlessly with zero code
Integrate into visualization tools without writing a single line
Because a true Data Mesh isn't about propping up old bottlenecks with shiny buzzwords. It's about giving business teams the ability to have a conversation with their data and act fast.
Join a Data Conversation,
Lili Marsh.
Lili Marsh.
References
- Gartner (2023): Why Only 48% of Digital Initiatives Deliver Business Value
- McKinsey (2023): AI-enabled Data Platforms Accelerate Time-to-Insight
- Forrester (2024): The State of AI in Data Management
- BARC Germany (2025): Data Mesh and Data Products Industry Study