Data Catalog

A data catalog is a centralized platform that collects and organizes metadata from across an organization’s data ecosystem. Instead of moving data into one repository, it indexes metadata from databases, data warehouses, BI tools, and applications so users can locate and understand data where it already exists.

OvalEdge’s data catalog brings this information into a single searchable platform, helping teams discover datasets, understand lineage and ownership, and collaborate on definitions and policies. This improves data trust, reduces time spent searching for information, and enables more reliable analytics and AI initiatives.

A data catalog improves discovery by indexing metadata across systems and making it searchable through a single interface. Instead of navigating multiple tools and databases, users can search for datasets using keywords, filters, or natural language queries.

OvalEdge enhances this process with AI agents, Google-style search, guided exploration, and domain-based navigation. Users can quickly locate datasets, reports, and pipelines while also viewing usage information, ownership, and business context to determine whether the data is trustworthy and relevant.

Finding data is only the first step. Teams also need context to determine whether that data can be trusted.

OvalEdge provides detailed data profiles that combine technical metadata with business context. Each asset can include lineage, relationships with other datasets, usage metrics, governance policies, business definitions, and comments from subject-matter experts. This allows analysts, engineers, and business users to understand how data is created, how it is used, and whether it is suitable for their analysis.

Yes. OvalEdge connects to more than 150 native data sources across databases, cloud platforms, BI tools, CRMs, ERPs, and data pipelines.

These connectors automatically harvest metadata from the systems where data already lives. This allows organizations to build a comprehensive catalog without moving or duplicating the data itself, while maintaining visibility across their entire data ecosystem.

OvalEdge captures two types of metadata to provide a complete understanding of data assets.

Active metadata is automatically collected from operational systems and reflects how data is used. This includes information such as query activity, access logs, and usage patterns.

Extended metadata adds business context to that technical information. It includes business definitions, ownership, governance policies, classifications, and domain information.

By combining both, OvalEdge helps organizations understand not just what data exists, but how it is used, governed, and trusted across the business.

OvalEdge embeds governance capabilities directly into the catalog. The agentic data governance platform automatically generates lineage, detects sensitive data such as personally identifiable information (PII), and links governance policies to data assets using AI agents.

These capabilities help organizations track how data flows across systems, classify sensitive information, and enforce appropriate access controls. By connecting metadata with policies and stewardship workflows, organizations can maintain regulatory compliance and ensure data is used responsibly.

OvalEdge goes beyond documenting governance policies. It operationalizes governance by linking policies directly to data assets and workflows.

For example, when sensitive data is detected or classified, policies can trigger access approvals, stewardship review, or masking requirements. Access requests can also be managed within the catalog and integrated with tools like Jira or ServiceNow, ensuring governance processes are enforced consistently.

OvalEdge automatically generates end-to-end data lineage across databases, pipelines, dashboards, and reports.

Before modifying a table or column, users can view downstream dependencies to understand which analytics assets, reports, or business processes rely on that data. This visibility helps teams evaluate the potential impact of changes and reduce the risk of breaking dashboards or data pipelines.

OvalEdge enables organizations to assign ownership and stewardship responsibilities at the domain, schema, or dataset level.

This allows governance responsibilities to be distributed across domain teams while maintaining centralized visibility across the data environment. Domain owners can curate and manage their data assets while the broader organization retains a unified view of metadata, policies, and usage.

Organizations typically begin seeing value quickly because OvalEdge automates many of the foundational catalog tasks.

Metadata harvesting, lineage generation, and classification are automated from the start, allowing teams to quickly index their data ecosystem. Business users can then search and access trusted data, while governance teams reduce the manual effort required to document and manage metadata.

OvalEdge monitors metadata ingestion and logs connector activity to ensure reliability. If a connector temporarily fails or a source system becomes unavailable, administrators are alerted so the issue can be resolved quickly.

Previously captured metadata remains available in the catalog, and incremental harvesting resumes once connectivity is restored. This ensures users can continue discovering and researching data assets even during temporary source system interruptions.