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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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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. This unified experience optimizes the process of developing and deploying ML models by streamlining workflows for increased efficiency.

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7 famous analytics and AI disasters

CIO Business Intelligence

According to CIO’s State of the CIO 2022 report, 35% of IT leaders say that data and business analytics will drive the most IT investment at their organization this year. And 20% of IT leaders say machine learning/artificial intelligence will drive the most IT investment. AI algorithms identify everything but COVID-19.

Analytics 145
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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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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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How to Choose the Best Analytics Platform, and Empower Business-Driven Analytics

Grooper

Connect the Dots Between Data Literacy, ISL, and the Requirements List. Data literacy is solved by a structured program of learning information as a second language (ISL). ISL eliminates data literacy by modeling the way we learn spoken language. Applied Analytics. Data science skills.

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Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics

AWS Big Data

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process.