Enterprise Semantic Layer
Consolidate metadata with a catalog of catalogs.
Govern and use all your data dynamically with semantics.
Scale LLM and AI initiatives.
Collecting metadata from technical, business and operational metadata into a single semantic layer provides context for data by representing its meaning, business significance, and relationships with other data. Simply put, when metadata is available in an effective way, data becomes more valuable.
TopBraid EDG makes it possible for organizations to:
- Understand your data: Connect data silos and trace data lineage across all business systems
- Increase productivity: Through understanding the impact of proposed data changes and enabling collaboration between business and technical stakeholders
- Improve business decisions: Create digital twins to combine, integrate, exchange and analyze information more effectively and reliably
- Reduce business risks: By knowing how – and when – you can use and share the data
Related Knowledge
How TopQuadrant is embracing Large Language Models (LLMs)
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Enhancing Data Interoperability in Life Sciences
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The Road to AI Success: Avoiding Common Pitfalls in Enterprise AI Pilots
Resource Hub Search Table of Contents < All Topics Main Data Governance The Road to AI Success: Avoiding Common Pitfalls in Enterprise AI Pilots Print
From Hype to Reality: How Ontologies Are Paving the Way for Enterprise AI
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What Are Classonomies – and why you may want to avoid them
Many of our customers have told us of the challenges of working with classonomies. To better understand what I mean by a classonomy, read this blog.
Why I Use SHACL For Defining Ontology Models
This is the second blog on what modeling language we recommend to use when creating ontologies. In this blog I will talk about what I do use.