🚀 Meet Data Mesh: our Data-as-a-Product future 👩🏻💻🤖👨🏽💻
Hello Data & AI friends! In this edition of Hiring Insights: Data, AI & Us I’d like to introduce you to a concept I am very excited about – Data Mesh! Back in 2019, Zhamak Dehghani, then the visionary Director of Emerging Technologies at Thoughtworks, introduced this game-changer. She saw a problem: our data architecture was like a closed club – centralized and monolithic, keeping data producers and consumers worlds apart.
Why we need Data Mesh now
Fast forward to today, and data has become more abundant, and our use cases for it more complex and variable. It’s not just about business intelligence anymore; it’s helping design products, streamline workflows, and boost employee power. The existing architecture lacked the flexibility to optimally serve all those consumers of data. That’s where Data Mesh enters the game! 🚀
„Convergence: the paradigm shift for building the next data platforms“
Dehghani’s genius concept is a paradigm shift – a total game-changer! She suggests decentralizing data architecture, reframing data ownership, and presenting data as a product. „This isn’t just for show; it means each data chunk gets its own local owner and guardian, boosting quality and security. But the real shift is the idea of treating data like a product. And what does that kind of future look like: it offers self-service platforms for everyone! This doesn’t just make data more accessible; it practically weaves itself into the fabric of your entire organization on all levels … hence the name, Data Mesh 🌐🚀
„Traditional approaches to data can create a disconnect between data owners and users.“
The Core Principles of Data Mesh
Yes, Data Mesh is a massive shift in thinking and in how the organization runs. However, we can understand where, when and how we see Data Mesh through the following 4 core principles.
Domain Ownership: Traditional centralization places data responsibility on one team, creating bottlenecks. Data mesh advocates for decentralization through domain ownership, where those producing data also ensure its quality and readiness for consumption.
Data as a Product: Reframing data as a product involves applying product thinking to prepare data in ways most valuable to consumers. The data product includes code, metadata, and infrastructure, fulfilling specific conditions for discoverability, security, and interoperability.
Self-Serve Data Platforms: Data mesh introduces self-serve data infrastructure, agnostic to domains, and simplifies data provisioning complexities. This enables users with varying knowledge levels to access and use data, promoting autonomy through abstraction.
Federated Governance: To ensure interoperability, federated governance balances local autonomy with global conventions. While data mesh confers autonomy to domains, products, and interfaces, standardized rules are crucial for sustained interoperability.
„Data mesh architecture from 30,000 foot view“
The advantages with Data Mesh
When you see the advantages, you will understand why I am so excited about Data Mesh! Here are some of the most compelling reasons for adopting a data mesh over a more traditionally centralised architecture:
Greatly improved data quality and scalability
Higher resilience to tech outages
Access: it’s easier for everyone in your team to access and harness the power of your data, regardless of their data engineering skills.
No more central maintenance headaches or hierarchy! Each domain is the boss of its own node.
„We need to shift to a paradigm that draws from modern distributed architecture … treating data as a product.“
Zhamak Dehghani, Creator of Data Mesh
A New Philosophy
Shifting to a data mesh isn’t a singular tech upgrade; it’s a whole new way of thinking about your data game. It’s a design philosophy. And it affects how you build your infrastructure and implement technology. 💡🔄 In our work at Hibernian Recruitment GmbH we are looking at how Data Mesh affects the talent strategy and the organizational design of the future.
If you’re interested in learning more, I recommend a deeper dive beginning with these articles by Deghani explore the Data Mesh principles and Data Mesh architecture. More sources can be found on the original blog article here. Or send me a DM and I can share some more specific resources with you as well.
