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The Power of Graph Databases, Linked Data, and Graph Algorithms

Rocket-Powered Data Science

And this: perhaps the most powerful node in a graph model for real-world use cases might be “context”. How does one express “context” in a data model? Hence, the graph model can be applied productively and effectively in numerous network analysis use cases. Ahh, that’s the topic for another article.

Metadata 250
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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Winkenbach said that his data showed that “deliveries in big cities are almost always improved by creating multi-tiered systems with smaller distribution centers spread out in several neighborhoods, or simply pre-designated parking spots in garages or lots where smaller vehicles can take packages the rest of the way.”

Big Data 275
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Minimizing Supply Chain Disruptions with Advanced Analytics

Cloudera

Advanced analytics and enterprise data empower companies to not only have a completely transparent view of movement of materials and products within their line of sight, but also leverage data from their suppliers to have a holistic view 2-3 tiers deep in the supply chain. Keep data lineage secure and governed.

Analytics 111
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Unlocking AI potential: The essential role of hybrid, multi-cloud strategies

CIO Business Intelligence

Notably, hyperscale companies are making substantial investments in AI and predictive analytics. AWS provides diverse pre-trained models for various generative tasks, including image, text, and music creation. AWS provides diverse pre-trained models for various generative tasks, including image, text, and music creation.

Strategy 105
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7 famous analytics and AI disasters

CIO Business Intelligence

Derek Driggs, a machine learning researcher at the University of Cambridge, together with his colleagues, published a paper in Nature Machine Intelligence that explored the use of deep learning models for diagnosing the virus. It mashed that data up with demographic data and third-party data it purchased.

Analytics 145
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Big Data Analytics Is The 21st Century’s Biggest Disruptor In Healthcare

Smart Data Collective

The healthcare sector is heavily dependent on advances in big data. Healthcare organizations are using predictive analytics , machine learning, and AI to improve patient outcomes, yield more accurate diagnoses and find more cost-effective operating models. Big Data is Carrying Massive Changes for Healthcare Organizations.

Big Data 101
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How to choose the best AI platform

IBM Big Data Hub

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.