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 |
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Hi past, present or future data professional! If you’re in the U.S., Happy Thanksgiving! I’m prepping for my food coma, so I’ll make this week’s newsletter quick. Like millions of Americans, I’ll be watching NFL football (go Ravens!). The average NFL game is 3 hours. If you can skip just one of today’s games and carve out that time for professional development, here’s how I’d spend it. In the spirit of football, I’ll split the time designation into 4 quarters. Documentation pass - if you read...
Extract. Transform. Read. A newsletter from PipelineToDE Hi past, present or future data professional! In 2 weeks or so The Oxford English Dictionary will reveal its 2025 word of the year, a semi-democratic process that lends academic legitimacy to words like “rizz” (2023’s pick). If you’re currently employed or interact with white collar workers, you would think the word of the year is “headwinds.” Used in a sentence: “We’ve pivoted our AI strategy but still encountered headwinds that...
Extract. Transform. Read. A newsletter from PipelineToDE Hi past, present or future data professional! After choosing a dataset, one of the most significant decisions you must make when creating displayable work is: How am I going to build this thing? For some, you may try to “vibe code” along with an LLM doing the grunt technical work. If you choose this approach, be warned: Nearly half of all “vibe code” generated contains security vulnerabilities and that’s before you even consider its...