Remove Knowledge Discovery Remove Metadata Remove Visualization
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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. Again, the overall aim is to extract knowledge from data and, through algorithms based on artificial intelligence, to assist medical professionals in routine diagnostics processes.

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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

This means the creation of reusable data services, machine-readable semantic metadata and APIs that ensure the integration and orchestration of data across the organization and with third-party external data. Knowledge Graphs are the Warp and Weft of a Data Fabric. This provides a solid foundation for efficient data integration.

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Why Establishing Data Context is the Key to Creating Competitive Advantage

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Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information. Without metadata management and other data-related operations with semantic technologies, organizations often struggle to connect data sets and achieve a unified view of their enterprise data.

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Enrich your serverless data lake with Amazon Bedrock

AWS Big Data

These summaries, encapsulating key insights, are stored alongside the original content in the curated zone, enriching the organization’s data assets for further analysis, visualization, and informed decision-making. Explore the AWS Serverless Data Analytics Pipeline reference architecture and take advantage of the power of Amazon Bedrock.

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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. million users. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.

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Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success

Ontotext

As a result, contextualized information and graph technologies are gaining in popularity among analysts and businesses due to their ability to positively affect knowledge discovery and decision-making processes. The goal should be to create value without really caring what is being used at the backend.