Data Mesh and Federated Governance: Striking a Harmonious balance
One of the key aspects of a Data Mesh is federated governance, but what does that really mean? This often involves striking a balance between giving individual teams autonomy while also maintaining a centralized approach to ensure everyone is aligned and working towards the same goal. The concept of “federated data governance” has emerged as a solution to this challenge.
So what does it mean to have a “federated” approach to data governance? Simply put, a federated approach means that there are clear rules of engagement in place, but individual teams are empowered to work within those boundaries to find the best solutions for their specific needs. This approach is distinct from a completely centralized approach, where all teams are required to use the same services and solutions, and also different from a completely decentralized approach, where teams have complete freedom to do whatever they want.
In a federated approach, there is still a “spine” within the organization that defines the rules, but teams are free to innovate within those rules. For example, the central team may have developed a set of core tools, but individual teams can build extensions or new tools that are compliant with the central standards.
However, this autonomy does come with a responsibility to remain compliant with the central definition. Teams cannot simply build anything they want without considering the impact it may have on the overall organization. This balancing act between autonomy and centralization is what makes federated data management such a powerful approach.
The idea of federated data governance is particularly important for organizations with multiple product owners, as each owner will have their own specific needs and goals. By giving product owners some latitude to innovate within the product stack, the organization can benefit from a wider range of solutions and services, all of which are still aligned with the overall strategy.
CONCLUSION
Federated data management offers a unique approach to data management that balances the autonomy of individual teams with the centralized control necessary to ensure that everyone is working towards a common goal. By giving teams the freedom to innovate within defined boundaries, organizations can benefit from a wider range of solutions and services that are tailored to their specific needs.
