Navigating Boundless Data Streams With The Swim Kernel - Episode 98

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The conventional approach to analytics involves collecting large amounts of data that can be cleaned, followed by a separate step for analysis and interpretation. Unfortunately this strategy is not viable for handling real-time, real-world use cases such as traffic management or supply chain logistics. In this episode Simon Crosby, CTO of Swim Inc., explains how the SwimOS kernel and the enterprise data fabric built on top of it enable brand new use cases for instant insights. This was an eye opening conversation about how stateful computation of data streams from edge devices can reduce cost and complexity as compared to batch oriented workflows.

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Is it possible to get relevant industry experience on your own (not through working at a company)?

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Tobias Macey profile image
I'm a systems oriented cloud and data engineer with a propensity for Python.

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