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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

It has far-reaching implications as to how such applications should be developed and by whom: ML applications are directly exposed to the constantly changing real world through data, whereas traditional software operates in a simplified, static, abstract world which is directly constructed by the developer. This approach is not novel.

IT 342
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What is a DataOps Engineer?

DataKitchen

DataOps is a set of practices, cultural norms and architecture patterns that help data professionals deliver value quickly. DataOps enables: Rapid experimentation and innovation for the fastest delivery of new insights to customers. Clear measurement and monitoring of results. The data engineer builds data transformations.

Testing 152
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Best Web Analytics 2.0 Tools: Quantitative, Qualitative, Life Saving!

Occam's Razor

You'll measure Task Completion Rate in 4Q (below). You'll measure Share of Search using Insights for Search (below). Only a plea to obsessively obsess about measuring outcomes and compute economic value, not just revenue. Experimentation and Testing Tools [The "Why" – Part 1]. ."

Analytics 135