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Galileo emerges from stealth to streamline AI model development

TechCrunch

A separate Gartner report found that only 53% of projects make it from prototypes to production, presumably due in part to errors — a substantial loss, if one were to total up the spending. Galileo monitors the AI development processes, leveraging statistical algorithms to pinpoint potential points of system failure.

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Creating the Ultimate Data Orchestrator

StubHub

By Corey Reed, Head of Data Science & Satya Gandham, Machine Learning Engineering Manager When you serve millions of customers every year?—?averaging That extensive opportunity is further enhanced by our ongoing migration to the cloud which has created several new and exciting avenues to explore. averaging more than 1.3

Data 45
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2020: The Year Bee-hind Us

Honeycomb

This normalized parenting in a way I’ve never experienced in a job before: one point from today's incident review "what went well" section: > [employee] felt empowered to say "I'm parenting" and not step into the incident. Though our deploy velocity remained the same, the engineering org has been far from stagnant.

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2020: The Year Bee-hind Us

Honeycomb

This normalized parenting in a way I’ve never experienced in a job before: one point from today's incident review "what went well" section: > [employee] felt empowered to say "I'm parenting" and not step into the incident. Though our deploy velocity remained the same, the engineering org has been far from stagnant.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media - Ideas

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. The applications must be integrated to the surrounding business systems so ideas can be tested and validated in the real world in a controlled manner.

DevOps 144
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The Good and the Bad of Snowflake Data Warehouse

Altexsoft

The data journey from different source systems to a warehouse commonly happens in two ways — ETL and ELT. Initially built on top of the Amazon Web Services (AWS), Snowflake is also available on Google Cloud and Microsoft Azure. As such, it is considered cloud-agnostic. Examples are JSON, XML, and Avro files.