CData Semantic Layer
Deliver centralized data and consistent, governed access for analytics and AI
The CData Semantic Layer unifies fragmented enterprise data—across on-prem, cloud, and SaaS—into a single governed source of truth that drives both people and AI.
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Manage data and metadata through a single pane of glass
Powered by our Connectivity Engine, the CData Semantic Layer integrates with 270+ enterprise data sources and supports any integration style (including CDC, Reverse ETL, batch movement, or virtualization), while maintaining semantic consistency. Raw tables and APIs are cataloged and exposed as standardized business metrics, dimensions, and hierarchies, providing a consistent foundation for analytics and AI.
Unify business terms and relationships through an intelligent glossary
The Intelligent Business Glossary automatically pairs business definitions with the corresponding source data and metadata using AI. This creates a centralized hub for standardized terms, data lineage, and semantic relationships—ensuring BI tools and AI agents interpret data consistently. This structured knowledge base sets the stage for AI-ready data consumption.
Curate and share data through a centralized catalog
Curated datasets are reusable and can be published in the Business Data Shop, where business users can browse, request, and access them as data products. Integrated lineage views span both virtualized and physical data stores, giving users a complete picture of data origin, flow, and transformation. The catalog ensures that high-quality, policy-compliant metadata is consistently disseminated across the organization—enabling governed self-service for business stakeholders.
Self-service speed meets IT governance
IT enforces security, governance, and lineage centrally, while business teams self-serve and innovate freely. Built-in Security & Governance features include dynamic role-based controls, row- and column-level masking, and explainable audit trails. Automated classification and extensible policy frameworks ensure that governance scales to future AI agent access patterns without slowing down innovation.
— Marco van der Winden, Manager, Corporate Data Management, PGGM
Why enterprises choose CData for semantic modeling
Unified, governed access to all data
Integrate data from 270+ sources into a single semantic layer. CData supports any integration style, including Virtualization, ETL/ELT, CDC, and Reverse ETL while ensuring consistent definitions across every tool, user, and workflow.
Automated business-first modeling
The CData Connectivity Engine automatically translates raw tables and APIs into clear and consistent relational data, ready to disseminate organization-wide as business metrics, dimensions, and hierarchies for self-service analytics and AI.
High-performance MPP engine
Execute complex, distributed queries at scale with an enterprise-grade massively parallel processing engine built for high concurrency and fast response times.
Enterprise-grade governance
Apply role-based, row/column security, masking, and lineage once, and enforce it everywhere automatically.
AI-ready foundation
Embed rich metadata and business context so AI and ML systems interpret data accurately, reducing hallucinations and boosting reliability.
Take the next step
See how you can turn disparate data into insights 80% faster with a universal semantic layer.
