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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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IT leaders: What’s the gameplan as tech badly outpaces talent?

CIO

Gen AI-related job listings were particularly common in roles such as data scientists and data engineers, and in software development. Were building a department of AI engineering, mostly by bringing in people from data engineering and training them to work with gen AI and AI in general, says Daniel Avancini, Indiciums CDO.

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AI data readiness: C-suite fantasy, big IT problem

CIO

While there seems to be a disconnect between business leader expectations and IT practitioner experiences, the hype around generative AI may finally give CIOs and other IT leaders the resources they need to address longstanding data problems, says TerrenPeterson, vice president of data engineering at Capital One.

Data 201
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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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Ready to transform how your IT organization drives business outcomes with AIOps?

CIO

Observability builds on the growth of sophisticated IT monitoring tools, starting with the premise that the operational state of every network node should be understandable from its data outputs. Experience and deliberate cross-functional learning opportunities are needed for people to acquire these skills.

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Data Scientist vs Data Engineer: Differences and Why You Need Both

Altexsoft

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

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1. Streamlining Membership Data Engineering at Netflix with Psyberg

Netflix Tech

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. What is late-arriving data?