Remove Data Quality Remove Definition Remove Knowledge Discovery Remove Visualization
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Crafting a Knowledge Graph: The Semantic Data Modeling Way

Ontotext

Today, as the number of decision-makers recognizing the importance of more dynamic, contextually aware and intelligent information architectures is growing, so is the number of companies with solutions based on knowledge graphs. Yet, the concept of knowledge graphs still lives without an agreed-upon description or shared understanding.

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The Importance of the Semantic Knowledge Graph

Ontotext

Knowledge graphs are large networks of entities representing real-world objects, like people and organizations, and abstract concepts, like professions and topics, and their semantic relations and attributes. An ontology enriches data within a knowledge graph with context and meaning that humans and computers can interpret.

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Top Graph Use Cases and Enterprise Applications (with Real World Examples)

Ontotext

Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.