Remove 2019 Remove AWS Remove Data Observability
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Data Mesh Architecture and the Data Catalog

Alation

In contrast to this common, centralized approach, a data mesh architecture calls for responsibilities to be distributed to the people closest to the data. Signals around the quality and integrity of the data are essential if people are to understand and trust it. Examples include public cloud vendors like AWS, Azure, and GCP.

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Learnings From Building the ML Platform at Stitch Fix

The MLOps Blog

For example, let’s take Airflow , AWS SageMaker pipelines. We’re building on top of Hamilton, which is an open-source framework for describing data flows. Stefan: Back in 2019. Like they didn’t have to think about, you know, data observability, but look, if you provided those data, we captured things about it.

ML 52