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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media - Ideas

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. The new category is often called MLOps. This approach is not novel.

DevOps 143
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Data Mesh Architecture: Concept, Main Principles, and Implementation

Altexsoft

In between, there are data engineers managing the data infrastructure with ETL/ ELT processes and tools required to transform operational data into analytical ones. Each operational team hosts, transforms, and serves their data to consumers, using dedicated data engineers to help them out. It works like this.

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Two Tales

LaunchDarkly

Eric Pollmann: My name is Eric Pollmann, I amount a lifelong software engineer, currently the CTO and co-founder of ClearBrain, my co-founder Bilal right there in the back, and one of our teammates also, thanks for joining. It’s a mind-numbing array of API’s to manage. TRANSCRIPT. It’s really fun there as well.