Why I built Analyst Gym.
Hi, I’m Drew, and I built Analyst Gym so you can practice the part of the job AI can’t do for you.
The technical side is the new floor.
Over the last year or two, AI tools have made the technical side of analytics much easier. You used to be able to stand out by being great at SQL and building dashboards and reports. Now the tools do a lot of that, and fast. Excellent technical execution is the new floor. It’s expected.
So what does good look like now? It’s everything around the code: the decision-making, the communication, running the project, understanding the business. That’s what makes you a partner to your stakeholders, as opposed to a resource. It also determines how much you’re paid, whether you get promoted and where your career goes.
Finding the insight isn’t the job.
Analytics isn’t just running code or building reports. It isn’t even just finding insights. It’s turning data into a decision, and you don’t get to a decision just because you found something.
You have to work with people. You have to understand their priorities and incentives, communicate clearly, use good judgment and know the business you support. You can do analytics with technical skills alone. That doesn’t mean you’ll be good at it.
Why a daily drill.
On the job, you can spend days or weeks inside one project, using one part of your skill set. A short daily drill drops you into a different situation each day: a metric that moved, a request that isn’t what it seems, a stakeholder who wants a number. Repeated practice keeps those skills from stagnating, and it grows them.
Practice the judgment yourself, and when you do use AI, you’re using it from a place of strength, not weakness. Your work gets better, and so do your shots at promotion, better pay and standing out from other candidates and peers who outsource the judgment.
This isn’t where you learn SQL.
Analyst Gym doesn’t teach SQL, Python or any other technical skill. If that’s what you need, there are plenty of great places to learn it, and if you’re working toward your first analyst role, start there. You need that foundation to tell whether AI did the technical work right, because your name goes on the work either way.
This is for the rest of analytics, the parts that matter most in 2026: judgment, communication, knowing the business, and turning a finding into a decision.
What I do here.
I plan, edit and approve every drill, and I often make a lot of changes to get one right.
About me.
I started out in client success and tech support, then moved into workforce analysis and business intelligence. Since then I’ve been a lead analyst, an analytics manager and a staff analyst, at startups and large companies across retail, healthcare, travel, media and software. Today I’m a Principal Data Analyst for a large SaaS company.
Along the way I’ve built SQL and statistics training for analysts, run learning programs and mentored a lot of analysts on exactly these skills. I have a master’s in analytics from Georgia Tech. I also spent two years as a coach for data analysts.