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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

Coupled with search and multi-modal interaction, gen AI makes a great assistant. Various initiatives to create a knowledge graph of these systems have been only partially successful due to the depth of legacy knowledge, incomplete documentation and technical debt incurred over decades.

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Understanding Social And Collaborative Business Intelligence

datapine

This is done using interactive Business Intelligence and Analytics dashboards along with intuitive tools to improve data clarity. In collaborative business intelligence, the workers and business managers interact with each other in order to improve the communication system. What is Social Business Intelligence? Website Link: [link] .

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Designing a SemTech Proof-of-Concept: Get Ready for Our Next Live Online Training

Ontotext

But it has enriched us in terms of identifying key needs for those looking to build a simple prototype in order to demonstrate the power of semantic technology, linked data and knowledge graphs. Some of that journey has been recorded in a previous blog post. What This Training Is.

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Why Establishing Data Context is the Key to Creating Competitive Advantage

Ontotext

By establishing a layer on top of existing enterprise systems and data warehouses, semantic metadata unlocks incredible new ways to interact with information, forging new experiences out of exploration and discovery. Additionally, applying semantic metadata removes the vicious circle of drowning in data but thirsting for information.

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

Ontotext

Knowledge graphs can also enable the creation of “digital twins”, which make sense of the collected data from various sensors in different systems, spanning the entire vehicle lifecycle. Read our post: Okay, You Got a Knowledge Graph Built with Semantic Technology… And Now What?

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Designing a SemTech Proof-of-Concept: Get Ready for Our Next Live Online Training

Ontotext

But it has enriched us in terms of identifying key needs for those looking to build a simple prototype in order to demonstrate the power of semantic technology, linked data and knowledge graphs. Some of that journey has been recorded in a previous blog post. What This Training Is.

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GraphDB and metaphactory Part II: An RDF Database and A Knowledge Graph Platform in Action

Ontotext

This might be sufficient for information retrieval purposes and simple fact-checking, but if you want to get deeper insights, you need to have normalized data that allows analytics or machine interaction with it. Knowledge Graph Visualization and Exploration with metaphactory. Building a Knowledge Graph Application with metaphactory.