These Habits Will Make You a Better Data Analyst

Added: 2026-05-30

[00:00:00]These habits will make you a better data analyst, not a course, not a certificate, not the next portfolio project you keep telling yourself that you will start on Sunday. Most people will treat their data career like a lottery ticket, like one big thing is going to magically change everything, but that's just not how life works. What actually changed mine were small habits I repeated every single week that quietly made me better than most people around me. Not overnight, but consistently. And most people completely ignore them because they just don't look exciting. But these are the habits that took me from delivering pizzas and Amazon packages to building a six-figure career in data, and now helping other people with non-traditional backgrounds to break into it as well. So, I'm going to be giving you seven of them, plus three bonuses at the end that almost no one talks about. All right, so the first habit is actually something I almost did not want to share because it is part of my edge. While everyone else was speed running through another SQL course, I was actually reading business case studies from Harvard Business Review. I was learning the difference between gross margin and net margin. I was figuring out why a CFO would care about CAC payback periods and what a good churn rate looks like for a SaaS company versus an e-commerce company. Why? Well, because data without business context is just numbers, and numbers don't get you promoted. Nate Silver, the guy who built 538, literally wrote the book on prediction and said it flat out in his book, "Data is useless without context."

[00:01:26]That's it. That's the whole habit in one sentence. And Edward Deming, a statistician who basically invented modern quality management, took it one step further and said, "If you don't know how to ask the right question, you discover nothing." So, the data is really never the problem. It's the questions behind the data that is everything. And here's the proof.

[00:01:45]There's a piece by Dataquest where the founder said he interviewed almost 200 hiring managers and recruiters about what makes a strong entry-level data analyst. A certificate never even showed up in one of the transcripts, not one time. But, business acumen, asking the right questions, understanding the why, that came up constantly. Johns Hopkins, Coursera, every serious source on data analyst skills says the same thing.

[00:02:09]Business context is what separates the analyst who reports numbers from the analyst who drives actual decisions.

[00:02:15]Now, before I would walk into meetings or virtually in meetings and say, "Hey, conversion rate is down 8%." But, now I can walk in and say, "Conversion rate is down 8%, but it aligns exactly with our July pricing update." Same data, but completely different reaction in the room. So, how do you reach this level?

[00:02:34]It's actually pretty simple, and I would encourage you to start this today. Start reading Harvard Business Review case studies about an industry that you want to be a domain expert in, or just listen to an episode of a business podcast once a week while you're doing the dishes or on a drive. You will learn more about how companies actually operate in 30 minutes than most business schools camps will teach you in 3 months. This is exactly the kind of stuff I drill into the members of my community because the technical skills get you the interview, but the business thinking is what's going to get you the offer and the promotions to the high-paying roles.

[00:03:08]Anyway, let's keep going. All right, so habit number two, tell the story. You can build the most beautiful dashboard in the world, and if you can't walk into a room and explain what it means and what someone should do about it, it's just wallpaper at that point. Pretty wallpaper, but wallpaper that is useless. Simon Sinek said, "The best great leaders are great storytellers."

[00:03:27]And I will add this, too, great analysts are as well because that's exactly what the data shows. Almost every serious analysis of data analyst skills, Coursera, Quadractic, Johns Hopkins, every major industry blog, they all rank communication as one of the most important skills. And most of them rank it as the most important soft skills.

[00:03:47]Not SQL, not Python, communication. The analysts who grow the fastest in data are the ones who can turn a chart into an actual decision. Think about how a weather reporter works. They don't show you the raw atmospheric pressure data.

[00:04:00]They tell you, "Hey, bring an umbrella tomorrow." That's storytelling in a nutshell, really. That's the job.

[00:04:05]Practice it loud and proud. Talk to yourself in the mirror if you have to, or even record yourself with OBS like I'm doing myself right now. All right, so habit number four, build proof, not credentials. So, this one took me a while to figure out. For a long time, I was chasing the feeling of feeling qualified. One more certificate, one more course, one more credential. And I came in mostly exposed to formal educational backgrounds. If people didn't have a degree, or people didn't have, you know, this letter by their name, I figured that was really the only way to break into tech. Luckily, I was wrong about that. Because when you're on this rat race chasing all these credentials to feel more qualified, expecting that you're going to hit some threshold and someone from out of nowhere is going to officially tap you on the shoulder and say, "Hey, you're ready right now." That moment never comes. Nobody is coming to tell you that you're ready. A report found that 72% of hiring managers say a portfolio matters more than a certificate. Another one said that 87% of hiring managers say that they're more likely to interview candidates with a portfolio. So, I switched it up. Instead of chasing more validation, I focused on building more proof. So, real projects, dashboards I actually use, and presentations that I recorded, and written breakdowns of how I solved actual problems. Think about it from the other side for a second. If you were hiring a contractor to say renovate your kitchen, would you rather see their certificate from a home improvement class or photos of three kitchens that they actually renovated along with testimonials of actual verified previous customers? Exactly. So, build a portfolio version of those kitchen photos. Look at what we've covered so far. We're studying the business, we're solving problems, we're telling stories, and we're building proof. So, So of these are flashy, and none of them are certificates, and none of them is the one tool that changed everything.

[00:05:50]They're small, and they're a little boring, but they're the kind of things that you can start doing today, and that's really the whole point. Small habits that compound while most people are chasing shortcuts that just don't exist. So if you're still here at the halfway point, you're already better than 90% of people who clicked this video. Hit subscribe if you haven't. I make videos like this every single week breaking down what works for breaking into data. Three more tips coming, and the bonus number two is honestly the one I wish someone told me 5 years ago. All right, so habit number five, consistency is key. This is the boring one, but it's also the most important. So there's nothing flashy about showing up every day, even when you don't feel like it.

[00:06:25]No one is going viral for, "Hey, I practiced SQL for 45 minutes today when I was tired." But that's what built my career. A lot of people quit way too early. They expect these rapid results, they hit a plateau around month two or three, and then they bounce into something completely new. I understand that mastery comes from repetition and long-term consistency, not motivation.

[00:06:46]Motivation is just a feeling, and feelings come and go. James Clear put it perfectly in Atomic Habits, "You do not rise to the level of your goals, you fall to the level of your systems." Most people think they have a motivation problem, but they don't. They have a systems problem. Build the systems, and the consistency will then take care of itself. If you think about it like compound interest, if you save $50 a month, year one looks pathetic. Year 10, though, is life-changing. Your skills work the exact same way. The first six months of consistent practice feels like nothing's happening. And then suddenly people are calling you the expert, and you can't even remember when that switch flipped. All right, habit number six, chase feedback. So this one is also hard. I'm not going to pretend that it isn't. It feels terrible to hand someone your work and have them point out everything wrong with it. Huge shot to the ego. But I learned early on that feedback is one of the fastest ways to grow, and protecting your ego is one of the slowest ways. So I always ask for critiques on my projects, on my presentations, my dashboards, even my interview answers, and my communication skills. And I always try really hard to react to the feedback in a way that a scientist reacts to data, not the way a person reacts to an insult. Think about it this way. Professional athletes watch recordings of themselves losing. They study their mistakes on purpose, even in slow motion, with a coach pointing things out. They may not enjoy it, but they do it because it's the fastest path to getting better. Your work is the same, so get the feedback. have number seven, simplify complexity. If you can't explain it simply, you don't understand it well enough. That line is quoted from Albert Einstein, and it means what it says. That's the bar I hold myself to personally. Plain English, no jargon, no acronyms unless I can define them, and also if my audience can define them.

[00:08:27]None of that, "Well, as you can see from the multivariate regression energy that makes everyone in the room silently zone out." Not only that, you can also alienate yourself from the audience if you're saying things that they just don't comprehend as well. Because it really doesn't matter if you understand it, it only matters if your audience understands something. A piece on data soft skills put it like this. "Technical findings mean very little. If you can't translate their significance for the audience in front of you." Different audiences, different levels of technical understanding, the same level of insight has to land for all of them. So, here's an actual test that I use. Before I present something, I always ask myself, "Could I explain this to a five-year-old and still have them get the main point?"

[00:09:09]Not the raw data, not the methodology, the point. "We're spending money in the wrong place, and here's where to move it." That kind of thing. So, if you can't pass a five-year-old test yet, that's not a confidence problem, it's a clarity problem, and clarity is a skill that you can start building today. All right, so speaking of skills that you can build, I've got three more bonus habits for you. I didn't put these in the main seven because most people will just overlook them entirely, which is honestly the reason why they work so well. When everyone else is ignoring something, the person who actually does it stands out by default. So, consider these are cheat codes. All right, so bonus habit number one, always asking why. I'm naturally a but why person. If you're not, you can train on this.

[00:09:46]Constantly ask things. Why did this metric change? What caused this outcome?

[00:09:50]When a stakeholder says, "Why are my sales down?" most junior analysts will just pull up sales numbers and confirm that they're down and then send a chart.

[00:09:57]A great analyst pulls the numbers and notices that it's down for maybe one region and checks if a competitor just maybe opened there, looks at the timing of a price change, and comes back with, "Hey, sales are down 8% overall, entirely in this region, and it lines up with XYZ." Same question, but completely different answers. That's just curiosity doing the work. Bonus habit number two, check your work. This is what I mentioned in earlier video, and this is one habit that I wish I built way earlier. In data work, trust is everything. You can be the smartest person in the room, but if you send a report with the wrong number even once, where they're, "Hey, we lost $2 million when in actuality you only lost $200,000, people will always second-guess your work moving forward.

[00:10:40]Whether it's months or even years. I take this super seriously myself. I did quality assurance in the Navy, and I always maintained those same standards in my work today. I'd rather spend an extra 20 or 30 minutes sanity checking my numbers than spending the next quarter rebuilding my credibility. If you only build one habit from this entire video, let this be the one. It costs you nothing, but it compounds forever. All right, bonus habit number three, build your career. Most people treat their career like it's something that just naturally happens to them. I treated mine like it was something I was actually building. That meant I didn't just focus on the technical skills, I worked on my portfolio, my communication, my networking, everything. Being good at the job and being good at getting the job are two completely different skills, and you need both. All right, so zoom out one more time, no single breakthrough changed my career. There was no magical course, there was no magical certificate, there was no viral LinkedIn post that just suddenly opened every door. It was these habits repeated consistently, building and building over the years. If you're stuck right now, or if you've been learning data for months and you don't really feel closer to the career that you want, just be honest with yourself. It's probably not that you need another course, it's probably that you need to start doing a couple of these habits this week and stay consistent for longer than it feels comfortable. If you want help putting this into an actual plan and you want to work with me to launch your data career, click the link in the description to see if we're a fit to work together.

[00:12:01]Otherwise, I want you to stick around and watch this next video that goes into a deep dive on a step-by-step road map on how to launch your data career. See you there.