Like many undiagnosed data nerds, I didn’t choose Excel — Excel chose me. I’ve worked in marketing, product and operations, and data analysis has been one constant skill that has helped me succeed in each category. Let me tell you how my early love for Excel helped steer a path towards SQL and greater analytical self-sufficiency.
I’d seen the nice orderly grid in high school, but I didn’t write my first formula until a few years into my career, and I only started learning how to do that because it was so tedious to update things manually. I was lazy, but at some point, learning to write Excel formulas just seemed like it had to be easier than doing it all myself. Of course, once you start, you just can’t stop. The more you know, the more inefficient things start to seem.
The deeper I got, the more obvious Excel’s limits became. Data in Excel is easy to mess up. Formulas are (at least by default) crammed into this tiny little box at the top, making them hard to debug (but I guess you get good at spotting parentheses).
A few years later, I was doing analysis on user network data at a startup and my workflow had gotten stupid. I relied on somebody in engineering to pull the raw data, brought it into Excel, did a bunch of transformation and eventually got some interesting insights. But then, the next week, I had all new data and too much process to update the final report. This was when I decided it was time to figure out how to do more myself.
We were using MySQL, so I started out just by downloading that and working through the online manual. It was so different than Excel - When you opened up the desktop app, there wasn’t much to see, and what I did see relied on a lot of jargon. But fortunately, the introductory documentation was quite good. Piece by piece, I started to learn what each of those opaque phrases meant and how to see the data in the tables (and I built quite an impressive pet registry along the way). And then I turned my newfound skill to the more pressing questions around user behavior.
It took me a little while to build up to the level of skill I had in Excel, but once I got there, I moved past it quickly. I could do everything I needed to faster and more flexibly in SQL. And as the data changed, my growing bank of queries continued to be all I needed to track progress.
There are a ton of people out there whose Excel skills are on another level, and this is not about trying to argue that one tool is better than another. SQL is just the right tool for the kinds of analysis I’ve built a big part of my career on.
When you have a SQL user, you’re able to be more self-sufficient. Nobody in Analytics or Engineering needs to take time to pull data for you. You’re not limited by anybody else’s knowledge. When you have a question, you have the skills you need to answer it. And if you’re curious, you’ll find and answer then next and next and next questions from there.
Excel helped me build a foundational data literacy that translated very directly into SQL. I learned the importance of data structure, normalization, cleanliness. Writing those first formulas helped me learn how to break down analytical questions into discrete elements.
For many in Marketing Ops, Demand Gen, Sales Ops and RevOps, SQL has an air of mystery. It seems like a tool for “the other side of the house”. Meanwhile, I see many who seem to feel that way absolutely crushing in Excel. If this is you, I’m just here to encourage you to consider taking the leap. All the work you’ve put into Excel has already prepared you for SQL. The skill you’ve been building quietly in spreadsheets is more powerful than you think—and learning SQL is just the next unlock.
And if you need just a bit more encouragement, join me for a (free, of course) Webinar on April 9th where we’ll talk about the first steps on the SQL journey for GTM Ops. I’ll be joined by Rose and Audrey Baid to talk about why it has never been more important for Ops teams to fully control their data stack and how you can take the first steps to building the skills you’ll need to do so. Register for the event here.
Hope to see you there.
Stuart Frederich Smith, CMO of TigerEye has built a history of leading great teams and launching impactful campaigns. With more than two decades of experience in marketing, product and operations, Stuart is a cross-disciplinary leader committed to collaborative execution. He holds a BA in Film, Television & Theatre from the University of Notre Dame and lives with his family in Portland, OR.
