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The future of data: A 5-pillar approach to modern data management

CIO

This article proposes a methodology for organizations to implement a modern data management function that can be tailored to meet their unique needs. By modern, I refer to an engineering-driven methodology that fully capitalizes on automation and software engineering best practices.

Data 167
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Are you ready for MLOps? 🫵

Xebia

These days Data Science is not anymore a new domain by any means. The time when Hardvard Business Review posted the Data Scientist to be the “Sexiest Job of the 21st Century” is more than a decade ago [1]. In 2019 alone the Data Scientist job postings on Indeed rose by 256% [2]. Why is that?

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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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#ClouderaLife Spotlight: Amogh Desai, Software Engineer II

Cloudera

This month’s #ClouderaLife Spotlight features software engineer Amogh Desai. It also happens that the cloud providers update their instance types and deprecate them all the time leading to installation failures, making the customers feel that the software is faulty when truly it is the hardware.

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Technical interview platform Byteboard spins out of Google’s Area 120, takes on new funding

TechCrunch

The team noted at the time that the current process for interviewing software engineers didn’t really work for measuring how well someone would do in a day-to-day engineering job. A group of experienced engineers review and rate the interviews. The business took off following its 2019 debut.

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Why a data scientist is not a data engineer

O'Reilly Media - Ideas

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. Data engineering is not in the limelight.

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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. ” Chatterji has a background in data science, having worked at Google for three years at Google AI.