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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

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Part 2: OMG! Not another digital transformation article! Is it about the evolution from RIM to Content Services?

ARMA International

Now the Fourth Industrial Revolution [2] is “digitizing the farm”— that is, radically reimagining agriculture through big data analytics that help farmers increase crop yields and using artificial intelligence (AI) to monitor pests, plant diseases, soil nutrients, and other growing conditions. Intelligent Capture.

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Capgemini and IBM Ecosystem strengthen partnership for Drone-as-a-Service

IBM Big Data Hub

It can offer data on demand to different business units within an organization, with the help of various sensors and payloads. The services are activated through access management for data collection, analysis and event monitoring in existing drones which are managed by clients and businesses.

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Ephesoft Launches Context Driven Productivity at Enterprise Productivity Summit

Info Source

The event kicked off with Ephesoft founder and CEO Ike Kavas on “Breaking Boundaries: The State of Digital Transformation,” highlighting best practices and pitfalls seen in enterprise automation projects. Ephesoft CTO Kevin Harbauer presented “Applying Semantic Data to Enterprise Productivity” and unveiled the CDP discipline.