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The Enduring Significance of Data Modeling in the Modern Data-Driven Enterprise

erwin

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

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Do Large Language Models Dream of Knowledge Graphs – Impressions from Day 2 At SEMANTiCS 2023

Ontotext

Did you know that, if you add “take a deep breath” to a prompt, chances are you will get more accurate results from Large Language Models (LLMs)? Do Knowledge Graphs Dream of Large Language Models? I didn’t either. He shared the need for more research at the intersection of LLMs and knowledge graphs.

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You Cannot Get to the Moon on a Bike!

Ontotext

In Computer Science, we are trained to use the Okham razor – the simplest model of reality that can get the job done is the best one. Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this.

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Top 10 Key Features of BI Tools in 2020

FineReport

Metadata management. Users can centrally manage metadata, including searching, extracting, processing, storing, sharing metadata, and publishing metadata externally. The metadata here is focused on the dimensions, indicators, hierarchies, measures and other data required for business analysis.

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

Ontotext

The Semantic Web started in the late 90’s as a fascinating vision for a web of data, which is easy to interpret by both humans and machines. One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases. Take this restaurant, for example.

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How to Build Knowledge Graphs for Enterprise Applications with Two Industry Leaders

Ontotext

Enterprises generate an enormous amount of data and content every minute. Knowledge graphs allow organizations to enrich it with semantic metadata, making it ready to be used across teams and enterprise systems. Partner with PoolParty and GraphDB to build knowledge graphs for enterprise applications.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.