Data Executives

Govern Modular Data Platforms

Explore strategies for efficient management of modular and decentralized data platforms. Learn how to empower teams with self-serve data solutions while maintaining control and governance. Discover organizational structures, infrastructure as code, quality gateways, blueprints, computational governance, and data product catalogs for transparency and compliance.



The modern data landscape is experiencing a revolution. Businesses are increasingly embracing decentralized data platforms to manage the ever-expanding volume and complexity of their data. This shift unlocks scalability, performance, and resilience, but also introduces new challenges.

Traditionally, data management followed a centralized model. A single, dedicated data team was responsible for all data assets, offering efficiency for smaller organizations. However, this approach struggles to scale with growing data volumes and team sizes.

The data mesh paradigm emerged as a response to the limitations of centralized data management. It promotes a decentralized and modular approach where domain-specific teams own and manage data products relevant to their area of expertise. This fosters a culture of data ownership, deepens data understanding within individual teams, and promotes agility and innovation. However, it necessitates a shift towards collaborative governance models, like federated governance, to ensure consistency and quality across the distributed data landscape. Under this approach, domain teams manage their data while adhering to central policies defined by a data governance team.


A well-designed platform can deliver significant benefits. However, to achieve these benefits, it’s crucial to address the following needs:

Self-serve Data Platform

Empower teams to consume and produce data independently, fostering a data-driven culture and accelerating decision-making.

Maintain Control and Governance

Ensure consistent data quality, security, and compliance across distributed user groups, even with self-service capabilities.

Promote Data Reuse and Composability

Break down data silos by facilitating the discovery, reuse, and combination of existing data products.

Ensure Efficiency

Simplify development, reduce redundancy, and enhance overall DataOps efficiency by providing reusable and approved components.

How to

Building a successful distributed data platform requires a comprehensive approach that addresses the challenges of team structure, governance, and development efficiency.

  • Platform Team: Establishes and maintains the core data platform infrastructure, ensuring scalability, performance, and security.
  • Developer Teams: Own and develop data products within their domain expertise, fostering deep data understanding and rapid innovation.
  • Federated Governance Team: Sets enterprise-wide data governance standards and works collaboratively with domain teams to ensure data quality, consistency, and compliance across the distributed data landscape.

Implementing EaC ensures all platform configurations, data pipelines, and data product definitions are codified. This facilitates:

  • Standardization: Enforces consistency across the platform, minimizing errors and ensuring efficient data management.
  • Version Control: Tracks changes and enables rollbacks if necessary, maintaining control and stability.
  • Automation: Automates deployments and configuration management, saving time and resources for development teams.

Standardize the data product lifecycle to ensure quality and maintainability. Set protocols for deploying data products and actively monitoring their compliance to identify and address any issues promptly.

Develop reusable templates (blueprints) for common data product development tasks. This streamlines the process for developer teams, reduces redundant effort, and ensures consistency across data products.

Create a centralized repository for all data products within the platform. This catalog should:

  • Promote Reuse: Encourage teams to discover and utilize existing data products instead of creating duplicates, fostering efficiency and knowledge sharing.
  • Ensure Composability: Facilitate the assembly of complex data products from existing components, enabling the creation of more sophisticated insights.
  • Adherence to Governance: Promote transparency by showcasing data lineage, quality checks, and access controls for each data product, ensuring compliance with governance standards.

Blindata, with its seamless integration with the Open Data Mesh Platform, offers a powerful solution to meet these needs. By empowering domain teams, fostering collaboration through federated governance, and streamlining development with automation and standardization, Blindata helps you unlock the full potential of your distributed data landscape.