
We know what the work of the data practitioner is, right? It's everything from managing data ingestion to data governance to report development to experimental design to basic and advanced analytics. It's writing (or vibe-writing?) SQL or Python or R while also being adept at whatever data stack—no matter how modern—is at hand. Of course, it's a lot more, too! And that's the topic of this episode: the unofficial, often unheralded, but often quite important "shadow work" of the analyst—the myriad tasks required to effectively glue together all the data work that occurs out in broad daylight to enable the data to truly be useful at driving the business forward. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
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#296: Avoiding Major Oopsies: Twyman's Law, Intuition, and Valuing Accuracy Over Precision

#295: Research and Analytics: the Peanut Butter and Chocolate of Data?

#294: Adapting an Analytics Team to an AI World

#293: Tool Selection and the Unhelpfulness of Feature Comparisons
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