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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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Are You Harnessing the Power of SaaS BI Tools for Dynamic Data Access?

FineReport

When combined, SaaS BI tools enable users to conduct comprehensive data analysis using modern cloud BI technology , providing access to all data sources and the ability to compile online dashboards from mobile devices.

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

datapine

You can use big data analytics in logistics, for instance, to optimize routing, improve factory processes, and create razor-sharp efficiency across the entire supply chain. The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries.

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 109
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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 141
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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.

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How OLAP and AI can enable better business

IBM Big Data Hub

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

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