Remove Data Quality Remove Knowledge Discovery Remove Metadata Remove Modeling
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From Data Silos to Data Fabric with Knowledge Graphs

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The Data Fabric paradigm combines design principles and methodologies for building efficient, flexible and reliable data management ecosystems. Knowledge Graphs are the Warp and Weft of a Data Fabric. To implement any Data Fabric approach, it is essential to be able to understand the context of data.

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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

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Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises. from Q&A with Tim Berners-Lee ) Finally, Sumit highlighted the importance of knowledge graphs to advance semantic data architecture models that allow unified data access and empower flexible data integration.

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

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Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. Graph-based solutions further leverage the relationships among the entities involved to create a semantically enhanced machine learning model.

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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

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The Semantic Web started in the late 90’s as a fascinating vision for a web of data, which is easy to interpret by both humans and machines. One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases. Take this restaurant, for example.