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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

Connecting the data in a graph allows concepts and entities to complement each other’s description. Given a critical mass of domain knowledge and good level of connectivity, KG can serve as context that helps computers comprehend and manipulate data. Augment your data via reasoning, analytics and text analysis.

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

Ontotext

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Several factors are driving the adoption of knowledge graphs. Linked Data, subscriptions, purchased datasets, etc.).

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On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. Thanks to their might, now scientists and practitioners can develop innovative ways of collecting, storing, processing, and, ultimately, finding patterns in data. Certainly not!

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Knowledge Graphs and Healthcare

Ontotext

Compared with other industries, healthcare has a fair amount of structured data, which is helpful. Ontotext has years of experience transforming data into knowledge across a number of industries and especially in the healthcare sector. It is from those connections that new discoveries are made. Tried and Tested.

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

Ontotext

We rather see it as a new paradigm that is revolutionizing enterprise data integration and knowledge discovery. Providing a formal unified conceptual model, ontologies enable unified access to and correct interpretation of diverse information and greatly facilitate analytics, decision making and knowledge re-use.