Unified metadata management for data discovery and data governance on Google Cloud. Automatic detection, classification, and management of data assets.
What is Data Catalog?
Data Catalog is Google’s central metadata management service that helps enterprises understand, organize, and manage their growing data assets. In an era where companies store data across dozens of systems, it becomes increasingly difficult to maintain overview of which data resides where and who has access to it.
The service automatically crawls Google Cloud data sources such as BigQuery, Cloud Storage, and Pub/Sub, extracts technical metadata, and makes it searchable. Teams can additionally add business metadata as tags to capture business context. This bridges the gap between technical data assets and business understanding.
Data Catalog is more than just a search tool. The service enables data governance through Policy Tags that enforce access policies at the column level. Data Lineage shows how data flows through transformations. Sensitive Data Protection integration automatically identifies personally identifiable information. These features make Data Catalog the backbone of modern data governance strategies.
Common Use Cases
Data Discovery and Cataloging
For organizations with hundreds of BigQuery datasets and Cloud Storage buckets, manual metadata management is no longer practical. Data Catalog automatically crawls all data sources, captures schema information, and makes them discoverable through a central search. Data analysts can quickly find relevant datasets without knowing which project or region they’re stored in.
Metadata Management
Technical metadata alone is often insufficient. Data Catalog enables storing business metadata as tags: Who is the data owner? What is the update frequency of the dataset? Which business processes use this data? This information can be captured in a structured way and considered in searches.
Data Lineage Tracking
Data Lineage visually shows how data flows through BigQuery pipelines. Which tables are sources? Which transformations are applied? Which downstream systems consume the data? This transparency is essential for impact analysis: If a source schema changes, which systems are affected?
Data Governance and Compliance
Policy Tags enable centrally defining data protection policies and automatically enforcing them. A policy like “PII data visible only to GDPR officers” can be applied at the column level in BigQuery. Data Catalog ensures these policies apply consistently across all datasets.
Sensitive Data Identification
Integration with Sensitive Data Protection (formerly DLP API) enables automatic identification of personally identifiable information, credit card numbers, or other sensitive information. These detections can be stored as tags and considered in access policies.
Integration with innFactory
As a Google Cloud partner, innFactory supports you in implementing Data Catalog as a central element of your data governance strategy. We help with defining tagging strategies, integrating with existing systems, and automating metadata management processes.
Our expertise includes designing Policy Tag hierarchies for GDPR compliance, developing Custom Entry integrations for external data sources, and building data lineage pipelines for end-to-end transparency.
Contact us for consultation on Data Catalog and data governance on Google Cloud.
Available Tiers & Options
Standard
- Fully managed
- Automatic metadata discovery
- Integrated with BigQuery, Cloud Storage, Pub/Sub
- Tagging and classification
- Pricing varies by usage
- Limited customization for metadata schemas
Typical Use Cases
Technical Specifications
Frequently Asked Questions
What is Data Catalog?
Data Catalog is a fully managed metadata management service that automatically captures, organizes, and makes searchable metadata from Google Cloud data sources. The service supports data discovery, governance, and compliance through central cataloging of all data assets.
Which data sources does Data Catalog support?
Data Catalog natively supports BigQuery, Cloud Storage, Pub/Sub, Cloud SQL, Cloud Spanner, and other Google Cloud services. External data sources such as on-premises databases or other cloud platforms can be integrated via Custom Entries.
How does automatic metadata discovery work?
Data Catalog automatically crawls supported Google Cloud data sources and extracts technical metadata such as schema information, table names, and column types. Additionally, business metadata can be manually added as tags to capture business context.
What are Policy Tags and how are they used?
Policy Tags are special tags that can be linked to IAM policies to control access to sensitive data. They enable centrally defining data protection policies and automatically enforcing them at the column level in BigQuery. This is particularly relevant for GDPR compliance.
Can Data Catalog track data lineage?
Yes, Data Catalog offers data lineage features that show how data flows through different transformations and systems. This is particularly useful for impact analysis, troubleshooting, and compliance evidence. Lineage is automatically captured for BigQuery pipelines.
How is Data Catalog priced?
Data Catalog uses pay-per-use pricing based on the number of stored metadata entries and API calls. Automatically discovered metadata from BigQuery and other Google Cloud services is free. Only Custom Entries and additional tags are charged.
Is Data Catalog GDPR-compliant?
Yes, Data Catalog is available in EU regions and meets all GDPR requirements. Through Policy Tags and central metadata management, the service actively supports compliance with data protection regulations by enabling identification and protection of sensitive data.
What search capabilities does Data Catalog offer?
Data Catalog offers powerful full-text search across all metadata, including table names, column names, descriptions, and tags. Search supports wildcards, Boolean operators, and can be filtered by tags, data types, or data sources.
