Data mesh is a strategic approach to decentralized data management that provides standardized self-serve data products through a governance model. This enables data-driven organizations to achieve agile, comprehensive and secure data management.
Four main principles are fundamental in a data mesh system. The following first three principles have been covered in previous blog posts:
This post will cover the fourth principle, Federated Governance, which enables organizations to maintain a robust and active mesh ecosystem by ensuring system engagement, mitigating domain isolation, administering product standardization, and addressing platform operational needs.
What is Federated Governance?
Federated governance is the operating model of the data mesh architecture and allows for the optimum interoperability of the other mesh principles.
The federation comprises domain and platform representatives and representatives from relevant associates in the organization, such as legal, compliance, and security.
The representatives comprise a team tasked with developing the data mesh, platform policies, product development, and operating standards. These oversight tasks of the federated governance team ensure product and operational consistency and maintain interoperability within the data mesh ecosystem.
The governance team is responsible for developing the guide of operating standards for the data mesh. This guide should include how decisions are made and executed, conflicts are resolved, and global standards on platform process, product development, and quality are created.
For the ecosystem to function, federated governance interprets the mesh as an evolving ecosystem overseen globally but also allows for policy flexibility with domains in so much as global policy and standards are followed. In this way, domains are incentivized to innovate to develop high-value and useful products without the friction of high-level bureaucracy.
What Problems Does Federated Governance Address?
Data mesh helps organizations optimize data structure and movement by using independent domain team experts to develop valuable data products that are shared and discoverable on a self-serve platform.
However, for the mesh system to thrive, it needs rules and operational oversight to ensure consistency and value throughout the mesh.
Therefore, assembling a federated governance operating model allows for the proper interoperability of the mesh by addressing the following problems.
Domain stability: Ensures domains are compatible within the mesh system and operate under a unified operational umbrella.
Data product consistency: Safeguards against product inconsistency and enforces product quality standards and truthfulness.
Organization rules and compliance: The governance team upholds organizational compliance through the mesh asserting that the mesh components are secure and trusted.
Operational costs: The governance reduces costs by automating the operational compliance processes for the mesh, which decreases the need for manual operational intervention.
Federated Governance Role in Data Mesh
Think of governance as a steering committee where domains have decision-making autonomy around products and adhere to a global set of rules set forth by the governance team. The rules and policies are automated and embedded into all data products and the self-serve platform.
The organization’s specialized functions, such as legal and security, set global rules. The standardized rules’ overall objective is to ensure trust, security, and interoperability of the mesh. These standards, in turn, lead to a consistent experience that end-users have with organization data.
In the book Data Mesh: Delivering Data-Driven Value at Scale, author Zhamak Dehghani outlines three components for federated governance. These components help guide governance development and thinking.
System thinking: Accounts for the dynamic interconnectedness of the data mesh. When operational and policy decisions are made, governance considers the data product, domain autonomy, self-serve platform, and end users.
Computational Policies: The rule set for governance determine quality standards and how the standards are enforced and monitored. Governance influences both local and global policies. Likewise, the governance is incentive-based to ensure local and global policy adherence.
Federated Operating Model: The governance operating model is designed as a decentralized autonomous system governed by a set of rules and policies to ensure consistent quality and operational standards throughout the mesh. The global and local policies are set by a team of cross-functional representatives from domains and subject matter experts.
The Challenges of Federated Governance
As the fourth principle in the data mesh, federated governance addresses many challenges that are presented by previous principles. These benefits cannot be realized without handling one challenge presented by federated governance.
This challenge is the ability of the organization to embrace constant change as the mesh evolves and improves. Therefore, when implementing federated governance, it is essential to consult with change experts to help guide and set up the correct structure for your organization to embrace these changes.
Completing the Mesh
We have now covered what a data mesh is and the four core principles of a data mesh. However, to optimize the mesh, you need to start with quality data at the domain level.
Any mistake in quality can erode the value of a mesh and the self-serve data products. A small amount of poor data originating from one domain data source can spread throughout your enterprise and wreak havoc. Bad decisions, missed opportunities, tarnished brands, diminished credibility, financial audits, wasted time, and expenses may result.
For this reason, F4 has developed a fifth principle and solution to ensure quality data is realized at the source, thus ensuring optimized outputs of the mesh system. Stay tuned for our next blog post on how to ensure data quality at the source for optimal data products.