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Hi friends 👋

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A special Monday edition of Sanity Check! Just kidding. I am just late again.

What's important is I am enjoying sharing with you all and I hope you are enjoying it too.

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Passable Prose

What I have written

​Git Environmental Activism - Protect Our Branches​

This is my most technical post to date. I see analytical teams maturing by putting their transformations under version control. It’s great progress, but too often when pushed to hit a deadline individuals fall back into old bad habits. A quick reaction ends up in cascading consequences for the rest of the team. We must take action to protect our environment. We must protect our branches.

Read more

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Curated Columns

What I found interesting

​‘Non-data People’ by Annika Lewis

Annika’s article hit home for me. The idea of segmenting people into binary “data” or “non-data” people does not respect the unique set of capabilities we each offer. I’ve written about this in the silly simple question. Everyone has their thing - and that’s a good thing.

Annika helps data professionals empathize with others and offers suggestions for how others can better recognize data professionals’ work.
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​What your Data Team is Using by Technically

This article is a solid breakdown of the components that make up the modern data stack. At the most basic level, you need to understand:

1. Where your data comes from
2. Where your data goes
3. How to move your data
4. How to prepare your data
5. How to expose your data

They offer practical tools to solve for each level and drill into subsets to help clarify confusing nuances.
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​The Great Data Debate recorded at Fivetran’s Modern Data Stack conference

Lakes v. warehouses, analytics v. AI/ML, SQL v. everything else. I started listening without a team. Still, just like watching March Madness, I found myself swept up rooting for the underdog.

SQL and Data Warehouses are the experienced players in the data space but came across as the underdog. Fast-moving scrappy upstarts in the machine learning and Databricks ecosystem are threatening to overtake the existing paradigm. Bob pointed out SQL has seen these challengers before, overcame them in the past, and will do it again.

The thing everyone agrees on is there is plenty of overlap between the SQL and ML communities and consolidation of efforts would benefit everyone.

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Featured Forecast

What you can look forward to next

I have been noodling on "the promise of analytics." Why is it organizations need analytics? Can we understand the wants, needs, and desires of our audience as data professionals? Should be a fun theme that will run throughout the next edition of Sanity Check. Stay tuned.