Enterprise Knowledge Graph

Connected Intelligence for Strategic Advantage As organizations gather extensive volumes of diverse data across business lines, the opportunity to extract unified understanding grows exponentially. However, information residing in application silos or disconnected systems limits strategic perspective. An enterprise knowledge graph (EKG) addresses this challenge by establishing a virtual intelligence nucleus linking relevant entities and semantics from distributed sources.

Entity Linkage

AI algorithms identify and connect related entities like customers, products or assets referenced across diverse sources.

Relationship Extraction

Semantic annotations reveal how extracted entities interact based on text, behavioral and event data analysis.

Data Discovery

Search and browse graph embeddings to find connected information popular for analytics and system integration needs.

Process Automation

Predefined event-based rules trigger actions when graph relationships meet specific conditions.

Case study 1

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Go to Use Case Title

What Are the Advantages You Should Expect?

Context Awareness

Deeper insights emerge from exploring how different business facets interrelate beyond isolated viewpoints.

Knowledge Reuse

Common domains and taxonomies established in the EKG facilitate sharing understandings across divisions.

Data Virtualization

Applications and users leverage a virtual abstraction of truth computed dynamically from distributed sources.

Process Optimization

Automated decision-making based on relationship inferences improves consistency, compliance and resource allocation.

Enterprise Knowledge Graph

Case study 1

Go to Use Case Title

What Are the Advantages You Should Expect?

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