Reaching 20k+ readers on Medium and nearly 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.
You Can Build A Data Pipeline In <90 Min.
Extract. Transform. Read.A newsletter from Pipeline: Your Data Engineering ResourceHi past, present and future data professional! Since today is a U.S. holiday, I won’t take much of your time; the good news is that, when conducted efficiently, building a data pipeline doesn’t have to take days, weeks or months. In fact, you can build a data pipeline in as little as 90 minutes. Accelerating pipeline development depends on a thorough read of the documentation, a familiarity with your scripting language’s requests library and patience dealing with pesky data structures. If you think, during this time, engineers are heads-down, you may have watched The Social Network too many times; personally, I like a little external stimuli while coding, which is how I ended up building a full dashboard during another American pastime–a baseball game. My secret? Distilling data with clean views, which I recommend over bloated source tables for both aesthetic and performance reasons. Even optimizations like views have their limitations, leading to optimization ceilings. The best way to break through, aside from stubbornness, is a combination of incremental problem-solving and “big picture” data modeling to reassess resources and attack the problem completely. Since I don’t want you to have to work any harder today, here are the embedded links as text:
If you’re celebrating America today, happy 4th! Thanks for ingesting, -Zach |
Extract. Transform. Read.
Reaching 20k+ readers on Medium and nearly 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.
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! It’s hardly controversial to say debugging is everyone’s least favorite part of programming. One widely-used debugging method is the rubber duck method, popularized in Pragmatic Programming, which suggests you talk through your code, aloud, to an inanimate object. Being able to speak intelligently about what prompted a technical decision is one of the most underrated data engineering skills. One...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! If you’re like me, in school you were always envious of your classmates that may not have applied themselves academically but were “good test takers.” Fortunately (for them at least), these folks would likely do well on what is quietly becoming the SAT of programming the GCA, or General Coding Assessment. Now, the General Coding Assessment isn’t any kind of board certifying test like the Bar...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! While many tech-oriented companies have (in one way or another) reneged on remote working arrangements, my employer made an extreme gesture to demonstrate its commitment to the ongoing office-less lifestyle: It removed an entire floor of our two-floor New Jersey office space. Other companies, like Spotify, have unveiled slogans like “Our employees aren’t children. Spotify will continue working...