Subject archive for "it-and-data-science-alignment"

Data Science

Announcement: Domino is fully Kubernetes native

Last week we announced that Domino is now fully Kubernetes native.

By Nick Elprin2 min read

Data Science

Domino 3.0: New Features and User Experiences to Help the World Run on Models

This blog post introduces new Domino 3.0 features. Akansh Murthy is a Technical Product Manager at Domino and previously worked as a software engineer at Domino and Kareo.

By Akansh Murthy7 min read

Data Science

Data Quality Analytics

Scott Murdoch, PhD, Director of Data Science at HealthJoy, presents how data scientists can use distribution and modeling techniques to understand the pitfalls in their data and avoid making decisions based on dirty data.

By Domino17 min read

Data Science

Data Science != Software Engineering

Why understanding key differences between data science and engineering matters

By Domino3 min read

Data Science

The Cost of Doing Data Science on Laptops

At the heart of the data science process are the resource intensive tasks of modeling and validation. During these tasks, data scientists will try and discard thousands of temporary models to find the optimal configuration. Even for small data sets, this could take hours to process.

By Eduardo Ariño de la Rubia6 min read

Data Science

Data Science on AWS: Benefits and Common Pitfalls

More than two years ago, we wrote about the misguided fear of the cloud among many enterprise companies. How quickly things change! Today, every enterprise we work with is either using the cloud or in the process of moving there. We work with companies that insisted, just two years ago, that they “can’t use the cloud” — and are now undertaking strategic initiatives to have “real work in AWS by the end of 2017.” We see this happening across industries including finance, insurance, pharmaceuticals, retail, and even government.

By Nick Elprin4 min read

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