June 2021
Intermediate to advanced
264 pages
7h 19m
English
Content preview from 97 Things Every Data Engineer Should Know
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Chapter 65. Tech Should Take a Back Seat for Data Project Success
Andrew Stevenson
Data has always been a constant in my career. From my early days as a C++ developer tthrough my switch to data engineering, my experience managing increasing velocities and volumes of data for use cases such as high-frequency trading has forced me to lean on cutting-edge open source technologies.
I was one of the fortunate ones. I worked with an elite set of handsomely paid developers, at the peak of the big data revolution. Cutting-edge as we were, managing the technology wasn’t our biggest challenge. Our top challenge was understanding the business context and what to do with the technology. As a dev, I shouldn’t be expected to configure complex infrastructure, build and operate pipelines, and also be an expert in credit market risk.
Time and again, I witnessed business analysts sidelined in favor of data engineers who spent all day battling open source technologies with little or no familiarity with the context of the data or the intended outcome. The technology-first focus often led to Resume++, where technologists were empowered and enamored with technology rather than focusing on business objectives.
The result was slow progress, project failures, and budget overruns. This especially hurt businesses during the 2008 crash, and we’re seeing that impact again starting ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.