Data Mesh Strategy | Decentralising Data Ownership

As companies grow, the central data team often hits a wall. Different departments like Marketing, Logistics, and Finance are constantly waiting for the engineering team to add new data or fix old pipelines. The Data Mesh approach changes this dynamic entirely, shifting from “Platform as a Service” to “Data as a Product.”

The Bottleneck Problem

In the old way of doing things, one single team managed all the data. They were expected to be experts in everything, which is impossible. This led to:

Waiting Games: It could take weeks just to get a new column added to a report.
Misunderstandings: Engineers didn’t always understand the data they were working with, leading to errors.
Fragility: If one thing broke upstream, the whole pipeline would crash.

The 4 Pillars of Data Mesh

Data Mesh is built on four simple but powerful ideas:

1. Owners of the Data

Instead of sending all data to a central IT team, the people who create the data keep ownership of it. The Logistics team owns the “Shipments” data because they understand it best. They are responsible for making sure it’s accurate and available.

2. Data as a Product

This is the big game-changer. We treat data with the same care as a software product. A Data Product must be:

Easy to Find: Listed in a central catalogue that anyone can search.
Reliable: It needs to have guaranteed update times and quality checks.
Secure: Access is controlled automatically.

3. Self-Serve Platform

To stop every team from reinventing the wheel, a central platform team provides the tools everyone needs, like storage and compute power. This lets the domain teams focus on their data, not on managing servers.

4. Shared Standards

To make sure all these different data products can talk to each other, we need some global rules. Governance groups decide on these standards (like how to format a “User ID”), while the teams decide how to implement them.

Is Data Mesh Right for You?

Data Mesh isn’t a magic fix for everyone. It requires a big culture shift. But for large enterprises that are struggling to move fast enough, it’s often the only way to scale.

Signs you might need a Mesh:

You have more than 3 or 4 distinct business areas.
Your central data backlog is growing faster than you can hire engineers.
Teams are starting to build their own “Shadow IT” solutions because they can’t wait for IT.

Partner with the Experts

Moving to a Data Mesh is as much about people as it is about technology. Alps Agility has helped major companies navigate this change, setting up the frameworks and tools needed for success.