Remove Contextual Data Remove Data Quality Remove Publishing
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Enabling Integration and Interoperability Across the Grid with Knowledge Graphs

Ontotext

It also adds flexibility in accommodating new kinds of data, including metadata about existing data points that lets users infer new relationships and other facts about the data in the graph. Schemas are an example of how the right metadata can add value to the data it describes.

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What Makes Data-in-Motion Architectures a Must-Have for the Modern Enterprise

Cloudera

Enterprise stream management is the ability to manage an intermediary that can broker real-time data between any number of “publishing” sources and “subscribing” destinations. This capability converts large volumes of raw data into contextualized data that is ready for use in a business process.

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Your data’s wasted without predictive AI. Here’s how to fix that

CIO Business Intelligence

This is where we blend optimization engines, business rules, AI and contextual data to recommend or automate the best possible action. There are several consistent patterns Ive observed across transformation programs, and they often fall into one of four categories: data quality, data silos, governance gaps and cloud cost sprawl.