How to Learn Data Analytics
I’ve worked in analytics for 15 years now in a variety of different positions. Now I run my own consulting company in addition to teaching people about analytics skills and careers.
In the past, I've talked about how I learned data analytics (and continue to learn).
Today I want to talk about how to learn data analytics.
What would I do differently if I was starting completely over?
1. Decide How Technical to Be
The first thing I’d do if I was starting over is decide how technical I wanted to be.
There are many different directions you can go as a data analyst with dozens if not hundreds of niches. They also have different requirements.
I personally like a blend of working on highly technical issues and working some with others in the business.
Because of this, I’d learn a programming language.
2. Pick a Language or Tool
I’d pick Python. Here's why.
When I was learning analytics, I first learned SAS which was a good fit because it was what the company I was working at used.
I’d sign up for DataCamp and use that to start helping me build the framework of learning the language.
There are alternative options which are equally good depending on your skills and career goals.
If I was going into anything healthcare, I’d pick SAS to learn first.
If you do have specific goals or target jobs, take some time to look at their job descriptions.
What do they require? Focus your efforts here.
No Code Analytics
If you want to get into an analytics role without programming, then you’ll still need some tool to use.
In that case, I’d suggest learning Tableau or Power BI as these are great for performing analysis.
3. Build Math Skills
At the same time, assuming I was starting over and didn’t have a degree in math, I’d prioritize taking several math classes which would build my statistics skills.
No matter what tool you’re using to execute your analysis, it’s really important to understand the background to the work you’re doing.
4. Find Real World Problems
As I’m building these skills, I’d look for opportunities to implement them on real world problems.
If I was working with a programming language, I’d still make sure I new data visualization to help convey my findings.
I’d think about problems from a business perspective.
Even if using a random set of data, I’d consider how it could be useful to a business and how I could set a goal of solving a business related problem with it.
If I could do this on real business problems in my current role, even better.
5. Apply for Jobs
Finally, I’d start applying - internships, jobs, etc.
As part of that I’d make sure I had a great resume and LinkedIn that really conveyed my value to a business.
Resources for Learning Data Analytics
A few additional resources you might find helpful: