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Why Establishing Data Context is the Key to Creating Competitive Advantage

Ontotext

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. Get these wrong and chances are your enterprise processes and systems will suffer.

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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

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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. This can lead to operational cost cutting and improve competitiveness.

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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. Semantic Data Integration With GraphDB. Building a Knowledge Graph Application with metaphactory.

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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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Business Intelligence System: Definition, Application & Practice

FineReport

When we talk about business intelligence system, it normally includes the following components: data warehouse BI software Users with appropriate analytical. Data analysis and processing can be carried out while ensuring the correctness of data. Data Analysis. It is an active method of automatic discovery.