Today, I’m going to share the exact steps I would take if I were starting over in data analytics.
Data analytics is a great career choice. I’m so happy I made the jump 15+ years ago and have stuck with it for all these years.
Unfortunately, when I was just getting started back in the mid-2000s, there were limited resources to get started:
- Limited or no online courses. Definitely nothing free.
- No YouTube. No Twitter. No Instagram.
- Basic tools like Excel and Microsoft Access for most analytics projects.
Fortunately, data analysts starting today get all of the benefits of modern technology.
There are two types of data analysts: action takers, and sideliners.
Data analysts that just sit on the sidelines don’t do well:
- Never getting started
- Bouncing from tutorial to tutorial
- Endlessly saving Twitter threads to Notion
- Stuck on the sideline, watching others take action
Fortunately, there are so many resources for you to take action in your data analytics career journey.
Here are the exact steps I’d take if I were getting started today:
Step 1: Start with SQL
Learning everything you need to know about data analytics all at once is impossible.
Don’t even try. Instead, start with SQL. Head over to SQLBolt (it’s free) and start working on those practice problems.
Just get started with 30 minutes.
Then 30 minutes more tomorrow. After a few days, you will start to get the hang of it. Start sharing what you are learning and if you get stuck, reach out for help on Twitter.
Unfortunately, many aspiring analysts just won’t stick to learning SQL.
They get distracted by other languages that so-called “experts” say are the next best thing. Don’t get distracted. Don’t procrastinate.
If you learn SQL first and share what you learn with others, it’s impossible to get stuck on the sidelines.
Step 2: Build In Public
So many aspiring data analysts just keep their journey to themselves.
But this is the wrong approach in so many ways. There are entire communities of people (my favorites are on Twitter) that absolutely love helping others. And you can benefit by sharing what you learn.
You don’t have to be an “expert” to share what you learn online.
What does expert mean anyways? You can build in public as a learner and let others join in on the journey with you. It’s a lot more fun!
Step 3: Create An Online Portfolio
Having an online data analytics portfolio sets you apart from the crowd.
And they don’t have to be overcomplicated. You can create a simple website to host your portfolio, without having to code, and without having to spend a dime.
Now, you will need to have 5-10 projects to add to your portfolio. Here are some resources I recommend
- 6 Online Communities That Aspiring Data Analysts Can Use To Create An Awesome Portfolio
- 4 No-Code Websites to Build Your Data Analytics Portfolio — for Free
- How To Find Awesome Datasets For Your Data Analytics Portfolio
You’ll also need to know how to write about each of your projects in a way that will gain attention.
Step 4: Learn How To Write Well
This last step might be the most important because it brings Steps 1-3 together.
It can be tempting to think that all you need is technical skills and recruiters will come knocking on your door. That might have been true in the past, but not anymore.
Now you need to have both tech skills and soft skills:
- Collaboration
- Critical thinking
- Communication
- Problem-solving
These soft skills all require you to be able to write. And write well. Here’s what I mean:
If you can combine tech skills (SQL) and show your stuff (by building in public) in a collection of 5-10 projects (with your online portfolio) you are a few steps ahead of the game. Because very few people take the time to build an online portfolio.
Unfortunately, most aspiring data analysts stop there. They don’t realize how important soft skills are.
But learning how to write well is critical. And here are some resources I recommend:
- The Ultimate Guide To Start Writing Online (for sharing your work online)
- Everyday Business Storytelling (general communication)
- Bulletproof Problem Solving (for problem-solving)
- Ask Powerful Questions (for critical thinking)
Next Steps
- Head over to SQLBolt and practice for 30 minutes
- Share your journey on Twitter (DM me at @NewPrediction)
- Start working on 1 project for your portfolio
- Improve your soft skills by learning to write well
Whenever you’re ready, there are 3 ways I can help you:
- View all past issues of my newsletter here.
- If you’re ready to build your online data analytics portfolio, my 14-day Data Analytics Portfolio Playbook is for you.
- If you want actionable data analytics advice on your specific situation, book a 1:1 coaching session with me today.
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Hi Brian,
Is it possible to pursue a career in data analytics if I just started learning it in the age of 44? Are there many job vacancies in data analytics field that are remote and do not require a certain age limit? Actually I’ve worked in another field for more than 15 years and a year ago I stopped working. And now, due to family needs I need to have income, but in my country I’ts so difficult to find job in this age. So now I plan to look for a remote job and I have interest in data analytics and just started it by learning SQL. But I am just having doubts because of my age..