Collibra
Data governance and data intelligence platform
Collibra is a data governance and data intelligence platform that helps organizations catalog their data assets, track data lineage, define ownership and business glossaries, and enforce policies around data access and quality. It is used…
Definition
Collibra is a data governance and data intelligence platform that helps organizations catalog their data assets, track data lineage, define ownership and business glossaries, and enforce policies around data access and quality. It is used primarily by large enterprises needing to document and control how data is defined, used, and shared across many systems. Collibra addresses the organizational confusion that builds up once a company has many databases, warehouses, and applications, where it becomes unclear what a given field actually means, who owns it, and who should be allowed to access it.
Overview
Collibra addresses the organizational, rather than purely technical, side of data management: as companies accumulate data across many databases, warehouses, and applications, it becomes difficult to know what a given field actually means, who owns it, whether it is trustworthy, and who is allowed to access it. Collibra provides a data catalog where technical metadata, such as table and column names, is enriched with business context, such as plain-language definitions, ownership, and approved usage, creating a shared reference point across technical and non-technical staff. A core Collibra concept is the business glossary, a governed set of definitions for key business terms, such as active customer or net revenue, that different teams might otherwise define inconsistently. By linking these business terms to the actual technical data assets that implement them, Collibra aims to reduce ambiguity and disagreement about what specific metrics and fields mean across departments, which is a distinct problem from the technical data quality checks performed by tools like Great Expectations. Collibra also supports data lineage tracking, showing how data flows and transforms from source systems through pipelines into reports and dashboards, which helps with impact analysis, meaning understanding what breaks if a source table changes, and regulatory compliance, meaning demonstrating where sensitive data originates and travels. Policy and workflow features let organizations define approval processes for data access requests, classify data by sensitivity, and track compliance with regulations that require documented data handling practices. In practice, Collibra is used to build a searchable catalog of enterprise data assets, standardize business term definitions across departments, and manage access approval workflows for sensitive datasets, most often within large, regulated organizations. Because governance platforms like Collibra primarily organize and document metadata about data, rather than moving or transforming the data itself, they are typically deployed alongside, not instead of, data integration tools like Informatica or Fivetran and data quality tools like Great Expectations or Bigeye. Effective use often requires significant organizational commitment to maintaining the catalog and glossary, since these systems can become outdated if not actively curated, and the tool alone does not guarantee good governance without that ongoing effort. Collibra competes with other enterprise data governance platforms such as Alation and Informatica's governance offerings, differentiating itself with strong workflow and policy management capabilities aimed at regulated industries with formal governance requirements. Smaller organizations without formal compliance mandates or a dedicated governance team often find a lighter internal wiki or spreadsheet-based glossary sufficient rather than adopting a full governance platform.
Key Features
- Data catalog linking technical metadata to business context
- Governed business glossary defining shared organizational terminology
- Data lineage tracking across source systems, pipelines, and reports
- Policy and workflow tools for data access approval processes
- Data classification for identifying and protecting sensitive data
- Impact analysis showing downstream effects of upstream data changes
- Compliance support for documenting data handling practices
- Integration with data quality and integration tools across the stack