Introducing the TQ Data Foundation–the Context Layer for trusted, autonomous agents. [LEARN MORE]
This video provides an overview of the Home Page of TopBraid EDG and orients you in regards to the different navigation options.
See how TopQuadrant’s Databricks Unity catalog integration allows users to import metadata from their configured Databricks instance by creating a new data asset collection. Use AI Linking to automatically connect existing terms to new metadata. See how the TQ Asset Diagram enables visual creation of assets and instances of classes, making it easier to work with subject matter experts and brainstorm relationships at the instance level.
Data standardization transforms fragmented and inconsistent data into a trusted enterprise asset. By applying metadata, semantic models, ontologies, and governance, organizations ensure accuracy, interoperability, and compliance. This guide explains techniques, frameworks, and real-world examples to build consistent, AI-ready data across your enterprise.
Understand data compliance, why it matters for enterprises, and how to operationalize regulatory requirements using governance and metadata.
Learn what structured data is, why it matters for enterprises, and how it powers data governance, analytics, and AI initiatives at scale.
Discover what an AI data governance framework is and how enterprises use it to ensure responsible, compliant AI.
Discover how retrieval augmented generation (RAG) works, why it matters, and how enterprises use it to deliver trustworthy, context-aware AI outputs.
Use Cases
Industries
Initiatives
Controlled Vocabularies
