Aspiring Data Analyst: Don't Start By Learning About the Normal Distribution

For years, you've followed the path laid out for you, striving to please everyone around you. But where has that gotten you?

Don't get me wrong, your parents, friends, teachers, and neighbours mean well. However, trying to please everyone or following the common path can be a trap (no surprises there?). You've learned valuable lessons from them, but it's time to look around and notice: those who are truly excelling often forge their own paths.

So, you want to become a data analyst or data scientist—a great idea! You've spent hours sifting through courses, curriculum, and books, but you can't seem to find the perfect material. I'm not surprised. The ideal resource doesn't exist until you create it yourself. You already know this (right?) but it's worth repeating. The issue isn't a lack of resources or tools; we have those in abundance. What you need to remember is the essence of being a data scientist.

Your job as a data analyst is to solve problems. You are the data advocate (charming!), taking a problem, collecting relevant data, conducting analysis, and making recommendations. That's where your focus should be. It's not about the methods or tools, although they are important. Don't lose sight of what truly matters.

Why Starting with the Normal Distribution May Not Be Optimal

Learning about the normal distribution is just a means to an end (don't let anyone know this!). Yes, you might eventually need to understand it, but maybe not just yet.

Instead consider this effective approach (I never said you shouldn't take advice from anyone!):

1. Pick a Project: Choose something you care about (what you don't know what you like? pick one anyway). Collect relevant data and information about it.
2. Set Practical Goals: Define what you want to achieve. Don't worry (focus matters more here) too much about perfection; refine your goals as you work through the project.
3. Formulate Questions: Based on your goals, create a set of questions you want to answer.
4. Start Building: Begin finding answers. When you get stuck, and stuck you will be at times, identify what you don't know, learn it, and come back to your project. Avoid binge-watching YouTube; stay focused.
5. Repeat: Go through this process as many times as needed. Within a few weeks, depending on your commitment, you'll make significant progress.

Remember, even without the official title, you are a data analyst. The process above should confirm that. Along the way, sharpen your communication skills, they're crucial.

Tips for Building a Successful Mindset

1. Be Sceptical: Challenge conventional wisdom. Don't dismiss new ideas; try them and see if they work. And just so you know, if it doesn't work at first, try again.
2. Embrace Better Approaches: There's often a better way to do something, but it might come at a cost. Are you ready to pay the price (if you can't afford it don't beat yourself up)?
3. Apply the Pareto Principle: Focus on the most important aspects—the 20% (okay it's not exactly that, sometimes it can be as little as 1%) that yields 80% of the results.

Departing Thoughts

You have come a long way. Congratulate yourself for putting up with me.

So, don't start by learning about the normal distribution. You can do better, and I hope by now you realise it.

What are your thoughts on this approach?

How do you plan to stand out in a crowd where everyone is competing to be the same?

Share your insights below!