Remove Data Integration Remove Knowledge Discovery Remove Management
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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

The key to success is to start enhancing and augmenting content management systems (CMS) with additional features: semantic content and context. TAM management, like content management, begins with business strategy. My favorite approach to TAM creation and to modern data management in general is AI and machine learning (ML).

Strategy 267
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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

The Semantic Web, both as a research field and a technology stack, is seeing mainstream industry interest, especially with the knowledge graph concept emerging as a pillar for data well and efficiently managed. And what are the commercial implications of semantic technologies for enterprise data?

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Crafting a Knowledge Graph: The Semantic Data Modeling Way

Ontotext

Paradoxically, even without a shared definition and common methodology, the knowledge graph (and its discourse) has steadily settled in the discussion about data management, data integration and enterprise digital transformation. Maximize the usability of your data.

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Bridging the Gap Between Industries: The Power of Knowledge Graphs – Part I

Ontotext

It can apply automated reasoning to extract further knowledge and make new connections between different pieces of data. This model is used in various industries to enable seamless data integration, unification, analysis and sharing. Manufacturing and Industry 4.0 The possibilities are endless!

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Business Intelligence System: Definition, Application & Practice

FineReport

In daily work, when business develops to a relatively large scale, we will all face variable management problems. Among these problems, one is that the third party on market data analysis platform or enterprises’ own platforms have been unable to meet the needs of business development. Data Analysis. Data Visualization.

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GraphDB in Action: Navigating Knowledge About Living Spaces, Cyber-physical Environments and Skies 

Ontotext

This has enabled them to meet the requirements coming from heterogeneous data in building automation systems, the interoperability issues critical for design engineering and, last but not least, the challenges in air-traffic control. The framework addresses current data integration needs and prepares for future capability.

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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. 10 Steps toward a Data Fabric with Knowledge Graphs.