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 be offensive. Instead of myself or other team members getting defensive, it led to a productive conversation about not just refining our approach to ingestion, but also inspired talk of how we can manage stakeholder expectations and softly encourage them to “do more with less.” Fortunately, you don’t need to derail a meeting to leverage what I call a productive why. Asking occasional, tactful “whys” can position you as a critical thinker and thought leader (or at least an enthusiastic thought contributor) within your org. When appropriate, consider asking…
I realize you may not be in a professional role; nonetheless, I’ve found a lot of value can result from occasionally asking “why” even when you’re simply writing code. For instance, I was a habitual user of Pandas’ .append() method. Unfortunately, to my disappointment, Pandas 2.0 deprecated .append() in the past year. I easily could have panicked and said “Iterating and appending key values to an empty data frame is how I’ve always converted JSON to a data frame. What am I going to do?” But being forced to adapt to the change made me think about what prompted that habit initially. To learn what that motivation was plus how a simple "why" nearly left me tongue-tied in an interview, read the latest on Pipeline. And so you don’t have to question where those hyperlinks go, here they are as plain text.
Questions? zach@pipelinetode.com Thanks for ingesting, -Zach Quinn |
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! 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...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! The only thing worse than summer temperatures (if you’re in the western hemisphere, that is) is a summer job search. Conventionally, summer isn’t the best time to apply for work; you could probably tell this if you’re currently working and find yourself accepting an overwhelming amount of OOO cal invites. If you are braving the heat of the job market, I want to share a more targeted and...
Extract. Transform. Read. A newsletter from Pipeline Hi past, present or future data professional! Well, it finally happened; AI has replaced a build I created and I’ve been made redundant. Thankfully, the person that created the AI integration was also me. And I did this on personal time so this isn’t an apocalyptic scenario. I’ve previously written about a handful of tools I created to optimize the “busy work” of blogging. One of the ways is by adding links to past relevant articles and...