Organizations are increasingly recognizing the value of establishing trust in their data. However, one of the biggest challenges in data governance is translating abstract policies into concrete implementations. It often takes multiple teams, tools, and steps to bring policies to life in actual systems.

Traditionally, this process consists of a series of handoffs between analysts, data stewards, and data engineers, with requirements documented in plain language and then translated into executable code. This workflow, while functional, frequently results in bottlenecks as analysts and data stewards gain technical skills and seek greater autonomy in managing data quality.

To address these issues, organizations are focusing on domain-specific observability and collaborative check creation. By configuring monitoring systems around specific business domains, teams can effectively track critical metrics like data volume, schema consistency, and data freshness. This approach not only clarifies ownership for alert triage but it also transforms data quality management from a siloed engineering task to a collaborative effort that combines business context and technical execution. Such a shift is essential for fostering a culture of accountability and responsiveness in data quality initiatives.

Bridge Policy and Practice with Integrated Data Quality

The integration of governance frameworks with quality enforcement systems represents a significant step forward in operationalizing data quality. Many organizations use governance platforms to define policies and document critical data elements, but they frequently struggle to link these definitions with actual production checks. This disconnect can result in duplicated efforts and inconsistent standards.

Collibra serves as a powerful, metadata-driven platform that helps create a solid framework for data governance. To fully realize the value of this framework, more and more organizations are leveraging Soda's integration with Collibra to enforce governance policies, making data governance operational, collaborative, and seamlessly embedded into daily workflows.

How Soda's Bi-Directional Integration with Collibra Works

By integrating governance and quality platforms bidirectionally, organizations can automate the generation of executable data quality checks based on governance-defined policies.

The seamless integration between Soda and Collibra not only reduces the need for manual translation but also ensures that operational realities are accurately reflected in policy documentation, ultimately improving the effectiveness and scalability of data quality programs.

• Define data quality rules in Soda: Use Soda directly to define data quality rules and execute them as data quality checks directly.

• Define data quality rules in Collibra: Alternatively, business and governance teams can define rules and policies in Collibra.

• Soda executes and monitors data quality checks: Automated, technical enforcement at every stage of the data pipeline via no-code tools or as-code.

• Trusted data is labeled & integrated into Collibra: Data assets receive a trusted/checked status in Collibra, ensuring transparency for all users.

• Issues are routed for immediate action: Failed checks are sent to the right teams, preventing bad data from spreading.

Watch a 4-minute Walkthrough

Unite Business & Engineering with No-Code and AI-Powered Checks

Soda enables business teams to contribute to data quality without needing engineering expertise.

• No-code checks allow domain experts to define and validate rules without writing SQL.

• Soda AI Check Assistant translates natural language rules into executable quality checks.

• Collaboration workflows connect governance, data engineers, and business users seamlessly.

Execute Data Quality Rules in Real-Time

Soda documents all data quality checks in Collibra, and helps you translate Collibra-defined data quality rules into directly executable checks.

• Run checks in production to validate governed data in real-time.

• Run checks in development to prevent bad data from entering production.

• Integrate active Soda checks and all check results in Collibra in real-time.

Bi-Directional Metadata Sharing

Share data quality and ownership related metadata across Collibra and Soda, and use Collibra as central metadata repository.

• Assign data assets to the right owners across Collibra and Soda (e.g. to feed notification rules).

• Integrate custom Soda check attributes to Collibra for a seamless transition of context.

• Automatically document all Soda data quality checks in Collibra, next to check results.

Shift-Left with Collaborative Data Contracts

Instead of detecting data issues after they cause problems, Soda allows teams to enforce data quality upfront—making governance preventative rather than reactive.

• Circuit-break bad data before it reaches production.

• Prevent schema changes or missing data from breaking pipelines.

• Collaboratively create agreements between data producers and consumers in a unified interface.

Take Your Collibra Investment Further with Soda

Define data governance policies in Collibra, seamlessly execute data quality rules with Soda, and actively enforce data quality across pipelines and business workflows.

Discover the powerful bi-directional integration to operationalize data governance.

Schedule a demo with our team of specialists.

Watch Soda and Collibra in Action

In this session, Mathisse De Strooper, Director of Customer Engineering at Soda, walks you through how Collibra policies can automatically be transformed into executable checks in Soda.