🧐 Why we made CASE WHEN

As I’m sure you’re aware, newsletters are a pretty saturated space. As a matter of fact, it’s perfectly reasonable to ask yourself “why should I subscribe to this one? what makes it different and why is it worth my time?”

The answer lies in the question— it’s worth your time because it will save you time, not flood your inbox. CASE WHEN was inspired by current noise in the data space. I’m not new to hot takes, so here’s one— spend any amount of time on “data LinkedIn/Twitter” and you’ll encounter:

• Companies trying to sell you things 🧳

• Influencers trying to sell you things 🗣️

• Companies partnered with influencers trying to sell you things 🙉

Usually targeted at newcomers, they come with bylines like How I made $X/year at Y company, or How to break into Z. Sometimes, they read more like a Buzzfeed article than a piece of professional content, e.g. The top 5 ways you can [Insert fast way to make money here]. Data Engineering Reddit is not impressed and for good reason.

While social media algorithms can source useful content, they also show us noise. That noise is not just annoying, it’s detrimental. It wastes our time and increases our cognitive load. That, in turn, stresses us out. 😢

The point of a newsletter is twofold:

• Create and share useful ideas

• Resurface good content in a way that adds value

Aggregating content is for robots. Creating content is for humans.

I can’t fault these companies for using social media to their advantage, nor can I fault influencers for monetizing their audience— after all, each is creating some amount of value, however, I do see a gap.

There doesn’t exist a simple, well-curated publication that promotes and surfaces valuable content. At least, not one that doesn’t require a slack community or 45 minutes/post to digest.

That’s why we created CASE WHEN.

Every week, CASE WHEN will deliver you content about data. This might look like:

• New tools and tech we find interesting (not things people pay us to find interesting)

• The latest development in data, whether that be transformation, AI, or Databricks/Snowflake beef 🧱 ❄️ 🥩

• Common-sense guides and approaches to make your work easier or help your data team succeed

My guarantee to you is that every piece of content we deliver will be fun. I’m going to have fun making it and I’ll do everything possible to make sure it’s fun to read. The moment it stops being either of those things, it will go away— I promise. 💜

To the three of you that made it this far, feel free to drop me a note: let me know what you’d like to see or tell me I’m crazy. I can’t wait to make awesome content for y’all!

🤘 See you on the other side,

Matt