A Shuttlepod Ride with Data – Exploring the Frontiers of Data Mesh: Part 2
By Sachin Kulkarni, Executive Vice President – Head of Commercial & Specialty Insurance and MGA, Americas
This blog is Part 2 of the series Talking Data with Lt. Commander Data. In Part 1, Sachin Kulkarni shared his first encounter with Starfleet’s iconic android aboard a space station. Their conversation explored the parallels between Data’s role on the USS Enterprise and today’s insurance industry, particularly the challenges of managing operational versus analytical data. As the discussion turned toward data mesh architecture and its potential to bridge these worlds, Data invited Sachin to continue the dialogue. What follows is that journey.
As the shuttlepod gently lifted off the launch pad, I felt a strange mix of weightlessness and wonder. The stars shimmered outside the viewport, and Earth slowly receded into the distance. Data, ever composed, began to speak as if continuing a conversation we had paused just moments ago.
Data: “The concept of data mesh, Sach, is not just about technology. It is a socio-technical shift — one that requires rethinking how organizations perceive and manage data.”
Me: “So it’s not just about building better pipelines or using new tools?”
Data: “Precisely. Data mesh is built on four key principles: domain-oriented ownership, data as a product, self-serve data infrastructure, and federated computational governance. Each of these is essential to solving the scalability issues of centralized data platforms.”
As the shuttlepod glided past a satellite array, I leaned in, intrigued.
Me: “Let’s start with domain ownership. How does that work in practice?”
Data: “Think of each business unit — underwriting, claims, distribution — as a domain. In a data mesh, each domain is responsible for the data it generates. This means they own, maintain, and serve their data as a product to others. It’s a cultural shift — from consuming data to being accountable for its quality, discoverability, and usability.”
Me: “That sounds like a big change. How do you get people to buy into that?”
Data: “Change management is critical. It requires leadership to empower teams, provide training, and align incentives. Captain Picard, for example, didn’t just give orders — he inspired trust and autonomy. That’s what’s needed here too.”
The shuttlepod banked left, revealing a breathtaking view of a nebula in the distance.
Me: “And what about this idea of ‘data as a product’? That’s not how most teams think about data.”
Data: “Indeed. But in a mesh, data is treated like a product with consumers. That means it must have clear documentation, SLAs, versioning, and a feedback loop. Just like the Enterprise’s replicator wouldn’t serve you a meal without knowing your preferences, data products must be designed with the end user in mind.”
Me: “And the self-serve infrastructure?”
Data: “That’s the backbone. It’s about enabling domains to publish and consume data without needing a central team for every task. Think of it as the holodeck — powerful, flexible, and accessible to all crew members, regardless of technical skill.”
Me: “And governance?”
Data: “Federated governance ensures consistency without central bottlenecks. It’s like the Prime Directive — a shared set of principles that guide behavior across diverse teams.”
As we began our descent back to the station, I realized how much this journey had reshaped my thinking. Data mesh wasn’t just a new architecture — it was a new way of working, thinking, and collaborating.
Me: “Thank you, Data. This has been… enlightening.”
Data: “You are most welcome, Sach. Remember, the final frontier is not just space — it is understanding. And in that pursuit, data is your most powerful ally.”
As the shuttlepod docked, I stepped out with a renewed sense of purpose. The stars still shimmered, but now they seemed a little closer — and so did the future of data.
Read Part 1 here.
