Active metadata management for smarter assets

Metadata management is the process of organizing and maintaining “data about data” to improve data governance, quality, and accessibility across your enterprise. Actian provides comprehensive automation through:

• Built-in scanners and APIs that automatically collect, consolidate, and link metadata from your entire data ecosystem.
• 75+ pre-built connectors supporting Snowflake, Azure, AWS, Tableau, Power BI, SQL Server, Oracle, SAP, MongoDB, Databricks, and more.
• Daily synchronization ensures metadata reflects current system states without manual intervention.
• AI-powered classification that automatically categorizes and tags data assets based on content analysis.

This automation empowers organizations to maximize data visibility and governance at enterprise scale.

Actian Data Intelligence Platform revolutionizes metadata management through a federated knowledge graph architecture that creates intelligent, multilateral relationships between data assets across your entire ecosystem. We go beyond static documentation through dynamic, context-rich intelligence.

Key differentiators include:

• Knowledge graph technology that automatically understands relationships and delivers relevant search results catered to the user.
• Interactive 360-degree view allowing users to see all the relational connections of an asset.
• Dual application approach with Studio for data stewards and Explorer for business users.
• AI-powered recommendations that deliver relevant search results, and facilitate documentation through suggested tags.

Actian makes metadata management accessible to both technical and business users, democratizing data access across your organization.

Actian empowers data teams with automated metadata extraction that reduces manual documentation tasks through intelligent discovery and classification. The platform’s smart data inventory system automatically retrieves and collects enterprise metadata, creating a contextrich data landscape that accelerates time to insight through:

• Automated discovery that indexes new data assets as they appear across your infrastructure.
• Structure recognition that identifies data types, formats, and patterns automatically.
• Relationship mapping that captures connections between databases, applications, ETL processes, and reports.
• Automated tagging with smart recommendations that reduce manual overhead.

This approach facilitates consistent metadata quality while reducing manual effort required to maintain data inventories.

Actian operates as a central intelligence layer that enhances your existing data investments, empowering organizations to leverage current tools while gaining enhanced visibility and control.

Integration capabilities include:

• Quality solution synchronization that automatically integrates with your current data quality tools to display trust indicators.
• Real-time quality metrics enabling users to assess data trustworthiness before issues arise.
• API-first architecture providing comprehensive APIs for custom integrations and workflow automation.
• Infrastructure compatibility ensuring seamless integration with existing data warehouses, lakes, and analytical platforms.

Data quality features:

• Immediate visibility into data quality metrics directly from the discovery phase.
• Automated quality assessment that eliminates separate quality evaluation processes.
• Trust indicators that help data users make informed decisions quickly.
• Quality scoring integrated into search results and data asset profiles.

Actian’s integrated approach empowers your organization to maintain confidence in data-driven decisions while maximizing existing technology investments.

Actian Data Intelligence Platform transforms data governance from a burden into an agile, automated framework that empowers data stewards to deliver trusted, compliant, and secure enterprise data at scale.

Documentation capabilities:

• Template-driven documentation for predefined and custom item types with drag-and-drop interfaces.
• Custom properties and fields that align with organizational requirements and compliance standards.
• Automated business glossary enabling consistent terminology across your entire data ecosystem.
• Collaborative documentation allowing teams to add descriptions, links, and discuss data assets.

Governance automation:

• Smart recommendations for data classification and policy enforcement.
• Regulatory compliance support through automated identification and management of personal data assets.
• Role-based access controls that ensure appropriate governance without restricting necessary access.
• Audit trails that track all metadata changes and user interactions for compliance reporting.

Advanced governance features:

• Policy enforcement that automatically applies governance rules across your data ecosystem through a federated knowledge graph architecture.
• Data stewardship workflows that streamline governance tasks and approvals.
• Metadata lineage providing complete visibility for impact analysis and change management.

Our comprehensive governance approach makes governance an enabler rather than an obstacle to business success.

Metadata is the foundation that transforms AI from experimental models into production-ready, trustworthy systems.

Why metadata is essential for AI:

• Context: Metadata provides critical context that helps AI systems understand not just what data it, but how it should be used and combined with other data.
• Trust and Reliability: Rich metadata including descriptions, data quality indicators, and lineage information enables AI systems to produce context-aware trustworthy outcomes.
• Production Readiness: Without a metadata strategy, AI initiatives struggle to move from isolated experiments to scalable, production–ready solutions.

How Actian empowers AI-ready organizations:

• AI-Ready Data Foundation: The Actian Data Intelligence Platform creates clean, accessible, and governed data powered by comprehensive metadata management.
• Automated Context Enrichment: Built-in scanners automatically capture quality indicators, lineage, and documentation needed for AI model training.
• Knowledge Graph Intelligence: Federated knowledge graph technology produces the rich relationships and context that AI systems require for accurate interpretation.
• Trust Indicators Integration: Data quality metrics enable AI teams to assess data trustworthiness before model training or deployment.

Actian recognizes that successful AI deployment depends on metadata readiness, that’s why we create the dynamic connections between AI systems and enterprise data. Learn more about the Actian Data Intelligence Platform.