Data Quality Score

The gold standard of data quality

Certify the integrity of your most critical data at scale.

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Quantify the impact of data quality

Data producers can now standardize quality and accelerate data product ROI.

Improve data quality of all critical resources

Secoda provides a numeric score based on a real-time audit of the health of your most important data resources.

Elevate your data quality standards

Get insights and prescriptive guidance on how to improve the resource’s usability, reliability, accuracy, and stewardship.

Streamline data governance at scale

Prioritize high-impact governance initiatives and ensure all critical resources are maintained.

Deliver consistent and trustworthy data

Let data consumers self-serve with unwavering trust in the curated data they are working with.

Powerful automated workflows

Automatically identify stale resources to deprecate and manage tech debt and storage costs.

“The data quality score is really handy because it offers a quantifiable, discrete metric of how well things are documented.”

Matthew DiRe, Analytics at Homebot

Head of Data and Analytics

Build trust in your data

Empower your data consumers to make informed, confident decisions faster.

Improve analysis with reliable data

Transparent quality indicators eliminate guesswork and enable more accurate decisions.

Use your company data with confidence

Prevent wasted resources spent on rework and inaccurate analysis.

Navigate data independently

Immediately understand the relevance and accuracy of a data resource.

Integrate with your entire stack

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Strong, scalable, secure

Secoda upholds industry-leading security standards while being user-friendly, fast, and intuitive.

SOC 2 compliant

Self-hosting available

SAML, SSO, and MFA

SSH tunneling

Data encryption

Advanced admin tools

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FAQs

How can I create Data Quality Scores for all resources?

Secoda automatically provides a preliminary score for all assets once your data sources have been connected. No manual work is required.

How do you maintain Data Quality Scores at scale on a regular basis?

Automated workflows can be created to apply actions based on the Data Quality Score of a given resource. Automations are built on rules and logic that can be applied across your entire workspace to manage scaled data governance initiatives.

What types of automations are available to help maintain and improve data quality at scale?

Automated workflows can be triggered based on attributes of cataloged resources to perform actions such as generating documentation, assigning tags, updating access, etc. For example, when a table achieves a "Good" quality score, the system can automatically mark it as "Published" and "Verified." This helps users quickly identify which tables are confirmed as reliable and ready for business use.

How does monitoring and observability affect Data Quality Score?

Freshness and Accuracy are two of the four dimensions the Data Quality Score is built on. Monitors and data quality checks can be built and automated within Secoda so you don’t need a separate tool specifically for data observability.