Data Catalog

The data catalog your whole team will actually use

With Actian’s knowledge-graph-powered catalog, business users find what they’re looking for, engineers stop fielding requests, and AI projects get the context they need.

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Top companies trust Actian

Your AI depends on data—do you know where yours is?

70 %

of organizations don’t have ML-powered data cataloging

Source: Gartner

51 %

of organizations are still doing manual data inventory

Source: Gartner

5 x

more trust for explicitly modeled decisions by 2029

Source: Gartner

A catalog built for teams who use data, not just manage it

Most catalogs stall because technical teams build them for technical teams. Actian is designed for adoption by everyone from day one.

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Adoption not shelfware

A data catalog built for every user, not just engineers, gets used. Role-specific Studio and Explorer experiences mean business users find data without filing a ticket.

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Enable self-service data

An enterprise data marketplace with trusted and governed data products means your users can find the data they need for self-service analytics, fast.

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Be AI-ready

Rich, accurate metadata gives your AI projects the context they need to produce reliable results: lineage, business definitions, and usage patterns all in one place.

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Make compliance easier

Granular data lineage and a full PII inventory give compliance and risk teams the visibility they need, without waiting on a data engineer to pull it for them.

One data catalog, every use case covered

Improve your data’s searchability and availability

  • Context-aware search: It’s easier to find relevant data products, visualizations, definitions, and more because Actian’s search is powered by a federated knowledge graph—meaning results based on concepts, not just keywords.
  • Enterprise data marketplace: Your users can browse and discover trusted data products in a single central location, helping them independently find what they need and enabling self-serve analytics.
  • Automated assistance: Discoverability-boosting tasks like categorization, tagging, and updating metadata are faster and easier with built-in AI assistance and automated metadata harvesting and synchronization.
  • MCP server: See your data quality results in the AI assistants and agent workflows you’re already using: they’re easily (and securely) shareable via the MCP Server.
  • Cloud-native, federated approach: Actian Data Intelligence is accessible from any device because it’s a cloud-native platform.
improve data searchability

Upgrade your data governance capabilities

  • Business glossary: Create alignment between business and technical teams: build shared definitions for policies, KPIs, and critical business terms like current customer, active account, or net revenue in the business glossary.
  • Flexible models: Get powerful enrichment for your data with a flexible metadata template for documentation and an intuitive interface that visualizes relationships between objects, domains, data products, custom assets, glossary terms, and more.
  • Active metadata: Understand how complete your data catalog is, how it’s being used, and more with active metadata analytics.
  • Conversational analytics: Actian’s integrated AI Analyst lets users query your data and metadata in natural language and get results grounded in your data catalog and business definitions.
  • PII and security insight: Achieve compliance faster and protect your sensitive data with tools for security classification, PII identification, and tagging.
upgrade data governance capabilities

Boost your data engineering outcomes

  • Smart data lineage: Get better impact analysis and improved business continuity for projects like warehouse migrations, platform transitions, and schema changes when you’re supported by Actian’s smart lineage with field-level granularity.
  • Automated updates: Automatic metadata monitoring and synchronization ensure that your impact analysis and data quality troubleshooting are based on your most current metadata.
  • Business glossary: Business context is always close at hand with Actian’s unified data catalog and business glossary, while data curation and ownership assignments ensure that any questions go to the right people.
  • Data products: Your data teams spend less time answering one-off data requests when users can find trusted, documented data products in Actian’s enterprise data marketplace.
boost data engineering outcomes

Ensure AI-ready data

  • Single semantic layer: Align your data, metadata, and organization around a shared understanding based on a catalog with comprehensive taxonomy and ontology management.
  • Steward workflow support: Building a shared context layer is easy in Actian’s data catalog, which features a flexible metamodel template, an intuitive drag-and-drop interface, and visualizations powered by a knowledge graph.
  • Data quality and observability: Continuously qualify your data’s validity, verify its readiness, and assess its quality with data observability. AI assistance helps you quickly deploy proactive, shift-left quality rules with 100% coverage.
  • Trusted data products: Create, share, and discover customer-centric, contract-governed data products directly in the platform, or import and publish them: Actian supports the ODSC and ODPS standards.
ai-ready data

Actian Data Intelligence Platform product tour

The catalog that finds your data, wherever it lives

The more complete and more detailed your data catalog is, the better your AI and analytics can perform. Start building your AI-ready data catalog with Actian: we have native support for 100+ data sources, and your metadata will be automatically discovered and kept current.

Modern data stack sources (Snowflake, Redshift, S3)
Legacy data environments (on-premise)
Semi-structured data (JSON, Parquet)
High-performance engines (Iceberg)
Specialized and NoSQL databases (Cassandra, DynamoDB)
BI tools (PowerBI, Tableau)

Explore Connectors

The catalog that finds your data, wherever it lives

The more complete and more detailed your data catalog is, the better your AI and analytics can perform. Start building your AI-ready data catalog with Actian: we have native support for 100+ data sources, and your metadata will be automatically discovered and kept current.

Modern data stack sources (Snowflake, Redshift, S3)
Legacy data environments (on-premise)
Semi-structured data (JSON, Parquet)
High-performance engines (Iceberg)
Specialized and NoSQL databases (Cassandra, DynamoDB)
BI tools (PowerBI, Tableau)

Explore Connectors
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Tableau icon
Power BI icon
SQL Server icon
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Googel BigQuery
Informatica Data Integration
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Tableau icon
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Googel BigQuery
Informatica Data Integration
asana icon
Snowflake icon
Tableau icon
Power BI icon
SQL Server icon
Azure icon
Agile icon
DBT icon
Googel BigQuery
Informatica Data Integration
asana icon
Snowflake icon
Tableau icon
Power BI icon
SQL Server icon
Azure icon
Agile icon
DBT icon
Googel BigQuery
Informatica Data Integration
asana icon
Snowflake icon
Tableau icon
Power BI icon
SQL Server icon
Azure icon
Agile icon
DBT icon
Googel BigQuery
Informatica Data Integration
asana icon
Snowflake icon
Tableau icon
Power BI icon
SQL Server icon
Azure icon
Agile icon
DBT icon
Googel BigQuery
Informatica Data Integration
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PostgreSQL icon
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Fivetran icon
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DynamoDB icon
Oracle icon
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AWS logo
Databricks icon
PostgreSQL icon
Looker icon
Fivetran icon
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DynamoDB icon
Oracle icon
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MongoDB icon
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Databricks icon
PostgreSQL icon
Looker icon
Fivetran icon
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DynamoDB icon
Oracle icon
SAP icon
MongoDB icon
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AWS logo
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DynamoDB icon
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Trusted by data and AI leaders

Organizations worldwide rely on Actian’s data catalog to unlock value. Governance, quality, unified semantic context, active metadata—Actian’s intelligent data catalog has what’s needed for production-scale success with analytics and AI.

Up and Running in Weeks. Used by Everyone.

Most data catalogs collect dust. Book a 30-minute demo, and we’ll show you how Actian deploys in weeks, not months, and drives adoption across technical and business users alike. 

What you’ll see in the demo:

  • How a federated knowledge graph gives every user and AI model the context they need to trust your data.
  • What widespread adoption actually looks like in customer environments.
  • Why business users can find and trust data without filing a ticket.

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