The Latest From Pipeline: Your Data Engineering ResourceHi past, present or future data professional! One of the worst habits you can adapt in data engineering is to accept a tool or technology as a black box you’ll simply never understand. For me, for the longest time, this was virtual machines. I would commit and troubleshoot code that would run within a VM but never quite knew how to interact with it. Recently, I provisioned a Google Cloud Compute Engine instance for a junior teammate and learned how to simply and logically create a virtual environment that can boost compute power and accurately mimic production. The best part is, I’ve distilled this into a process that shouldn’t take you more than 5 minutes. Read the latest here. And if you want to learn why automation isn’t always the end goal of software engineering, read last week’s article. Thanks for ingesting, -Zach |
Top data engineering writer on Medium & Senior Data Engineer in media; I use my skills as a former journalist to demystify data science/programming concepts so beginners to professionals can target, land and excel in data-driven roles.
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! Despite falling into the realm of engineering, data infrastructure construction is a bit like basic art. At times building a data pipeline is as simple as filling in one of those color-by-numbers books. Other times, the process of extracting and ingesting data can be as abstract and disconnected as paint flicked onto a canvas, Jackson Pollack style. No matter the complexity of your build, there...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! To those in the U.S.: Happy Halloween! In the spirit of the spooky season, I’d like to scare—I mean warn—you about 3 truly creepy trends that might give you goosebumps during a job search. A Shady Recruiter “Ghost” Writing Your Resume When in the job market, one of the first things you learn, after how to write a resume, is how to format one. I’m sure you know about headings, bullet points, etc....
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! I recently participated in a technical design meeting that was derailed by a single, fundamental question. “Why?” Despite the fact that I worked with the particular data source we were discussing for nearly two years, I fell into the common trap of going “on autopilot” and failing to question the initial need for the data. At this point, you would think asking “why” of years’ worth of work would...