1 Google White Paper Every Aspiring Data Engineer Must Read

The story of Dremel and how it led to one of the most widely-used data engineering tools.

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In data science graduate school there was nothing I hated more than a textbook. It may be surprising to hear from someone who blogs as frequently as I do that my learning style never aligned with words on a page.

This is doubly true with code; I find textbooks covering programming concepts to be more akin to Mad Libs than learning materials that encourage both critical thinking and a degree of creativity. My exception to this aversion to code-related academic reading is a handful of white papers.

For those that have been fortunate enough not to spend an extended period of post-grad combing through abstracts and charts in academic publications, a white paper is a summary of a project or experiment. And the white paper I’ve placed in the must-read category relates to one of the tools I — and thousands of data engineers — use on a daily basis: BigQuery.

BTW, I’ll link it at the end of this piece.

While it’s not necessary that you, as an aspiring data engineer, grasp every formula and graph presented in the paper, it will nonetheless help inform how you think about cloud architecture and, as you’ll see…