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How Contextual Data is Driving the Future of Telehealth

TDAN

The expansion of big data applications has created opportunities across economic sectors. In healthcare, however, the potential of big data applications goes far beyond the financial. The contextual data gleaned from big data can drive healthcare solutions and accessibility to new heights.

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ETL vs ELT in 2022: Do they matter?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Data is ubiquitous in our modern life. Obtaining, structuring, and analyzing these data into new, relevant information is crucial in today’s world. The post ETL vs ELT in 2022: Do they matter?

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RAG – The Newest Advance in AI Is All About Context

Smart Data Collective

RAG is a great new breakthrough in AI that is changing the future of contextual data management.

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Oracle launches a new sustainability app for Fusion Cloud EPM

CIO Business Intelligence

Emission factor mapping and other capabilities As part of Oracle Fusion Cloud Sustainability, enterprises would get access to features such as automated transaction records, contextualized data, pre-built dashboards, emission factor mapping, and audit capabilities.

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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

Contextual data understanding Data systems often cause major problems in manufacturing firms. IBM built a workforce advisor that uses summarization and contextual data understanding with intent detection and multi-modal interaction. They are often disparate, siloed, and multi-modal.

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Alteryx works in generative AI for speedy analytics results

CIO Business Intelligence

The first, dubbed Magic Documents, applies AI to Alteryx’s Auto Insights feature, creating contextualized data visualizations in several forms, including PowerPoint, email and more. Alteryx’s AiDIN engine will power three new features, according to a company announcement Wednesday.

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Achieving Trusted AI in Manufacturing

Cloudera

Here are some of the key use cases: Predictive maintenance: With time series data (sensor data) coming from the equipment, historical maintenance logs, and other contextual data, you can predict how the equipment will behave and when the equipment or a component will fail. Eliminate data silos.