Query & Theory Newsletter

Remember when you used to have time to read all those data articles saved in your browser tabs? Yeah, we don't either. Which is why we’re launching the Query & Theory Newsletter - your monthly TL;DR of insights, resources, and things our team finds cool in the Fabi.ai world (and beyond 🧑‍🚀).  

[Guest blog] Your first data hire 

Aditya (data leader @ Shogun) and Marc (our CEO and co-founder) spent some time getting thoughts on paper about when to pull the trigger on your first data hire. TL;DR: Skip the data scientist (for now) and aim for someone who can both wrangle SQL and whisper strategy to your execs. At $240k+ per year, you'll want to make this hire counts. The article includes a foolproof 90-day plan to make sure your new hire hits the ground running.

[Video] 30-Second Sankey

Tired of boring bar charts? Good news: We have a lightning-fast guide to creating Sankey diagrams (those fancy flow charts that make your data look like a river system). No more wrestling with Plotly code - just organize your data in three columns and let AI do the heavy lifting. Because sometimes you need your data visualization to spark joy. ✨

[Blog] Python vs spreadsheets: The ultimate showdown 

While Excel warriors continue defending their million-row limits, we're here to tell you why Python might be your next best friend. In fairness, if a spreadsheet can do the job, stick with it. But when you're ready to graduate to custom visualizations and automated pipelines, Python's got your back. Plus, no more "Final_Final_v3_REAL" spreadsheet versions floating around.

[Community post] Mapping query costs to sources

Rob (warehouse platform eng. lead @ Canva) pulled back the curtain on how his team thinks about snowflake monitoring this month. Their team spent three years building a DIY solution (think custom query tags and dbt wizardry) before discovering they could've just used dbt-snowflake-monitoring. The real MVP? Metadata - turns out tracking every query's cost makes it way easier to convince folks to optimize their late-night data explorations.

Thanks and happy querying, 

The Fabi.ai team