Extract. Transform. Read.A newsletter from Pipeline: Your Data Engineering ResourceHi past, present or future data professional! For many, perhaps even yourself, it’s the most dreaded time of the year: Back to school. While data engineering doesn’t require “supplies”, it can be helpful to pick up a book or two. Aside from getting industry context, your latest data read can provide a helpful talking point in interviews or even impress in casual discussion. Though not quite a textbook, I highly recommend the book that opened my mind to the power and influence of data: Mindf*ck Cambridge Analytica And The Plot To Break America by fashion designer-turned data scientist Christopher Wiley. One of the most valuable lessons you can learn as a student is identifying what you won’t be taught. Despite its universality in data-driven orgs, SQL is under-taught in institutionalized data science curricula. Determining which skills you’ll have to learn on your own can help you prioritize your upskilling and even get you through the class from hell. And if you aren’t currently in school, picking the right certification can advance your career, while the wrong choice can lead to a cluttered LinkedIn profile—and mind. For those compiling a digital supply list, here are this week’s links as plain text:
Thanks for ingesting, -Zach |
Reaching 20k+ readers on Medium and over 3k learners by email, I draw on my 4 years of experience as a Senior Data Engineer to demystify data science, cloud and programming concepts while sharing job hunt strategies so you can land and excel in data-driven roles. Subscribe for 500 words of actionable advice every Thursday.
Hi fellow data professional! SQL Lite, the database you most likely learned SQL on, is built atop 100k lines of source code. Sound like a lot? Compare that to Chromium, the engine for Google Chrome, which boasts 30+ million lines of code under the hood. Shortly after acquiring Twitter/X, the world's first trillionaire, Elon Musk, famously asked engineers to tell him how many lines of code they wrote per day, igniting a debate among engineers throughout the software and data domains. When I...
Hi fellow data professional! If you read my note on Tuesday you’ll know I’m coming off of the data engineering week from hell that seeped into my personal life, and delayed the launch of something cool I was planning to share with you; if you want to know more about that, scroll to the end of this message. Last week a flagship data source had a major problem and since it’s within my ownership area, I was the one with the knowledge and responsibility to fix it. I wanted to share the experience...
Hi fellow data professional! Hardly a work day goes by without receiving a request from a data analyst. They range from the mundane “Can you add this column?” to the occasional emergency “The data didn’t load all weekend and the leadership call starts in 15 minutes!” At the end of a jam-packed week I received an unusual request: Help with a Python script. My teammate wanted to know: Best practices How to commit to GitHub What the best way to deploy is They admitted the task was simple,...