Knowledge Graph

Generate a 360° view of your assets and the relationships between them
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A knowledge graph is a data structure that represents a universe of knowledge: a collection of interlinked concepts, entities, relationships, and events. It gives context to data through the linking of semantic metadata to provide a framework for data integration, analysis, and sharing.

Knowledge Graph Schema

Accelerate your transition to a knowledge-centric organization with Zeenea

Our powerful knowledge graph combines flexibility and intuitive user experiences to deliver enhanced data discovery, governance, and greater value to your organization.

Get rich and in-depth search results

Zeenea’s powerful knowledge graph provides deeper and more relevant results of concepts, entities, and the relationships between them. Fueled by machine learning, our solution not only integrates the standard, flat, indexation of metadata but is also powered by an NLP layer, a semantic layer analysis, and a personalization layer that relies on user classification. Our technology understands complex searches found in multiple items using the relationships defined in the graph.

Knowledge Graph Get Rich And In Depth Search Results
Knowledge Graph Optimize Data Discovery

Optimize data discovery

Our knowledge graph facilitates the visibility & understanding of your enterprise data landscape. Our solution automatically identifies, classifies, and tracks data based on contextual factors – map your assets to key concepts to make them discoverable and accessible for risk management and regulatory compliance, or dig deeper into the data to uncover hidden relationships & patterns.

zeenea Explained #1

Powered by a Knowledge Graph

In under three minutes, Ole Olesen-Bagneux, author of ‘The Enterprise Data Catalog’ (O’Reilly) and Chief Evangelist at Zeenea, shares the how and why of Zeenea’s design, architecture, and technological choices through Zeenea Explained Series.

In this episode, learn about knowledge graphs, their capacities, and their integral role in the organization, search, and discovery of data.

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5 TECHNOLOGICAL BREAKTHROUGHS OF A NEXT-GEN DATA CATALOG

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