A Few Tips on Choosing the Right Career Path for You at Dataquest

When I started with Dataquest, I spent some time choosing which courses and carer paths I’d take. To this day, I still see people having the same question. As you can see in the topic, I had promised to write more about how to make this decision, so here I am.

Keep in mind that what you’ll read next is not carved in stone. It is only my opinion based on the courses I took and still take and on my experience working as a data practitioner. Feel free to disagree and to share your thoughts.

Also, I am not making a distinction between Python and R courses. This is a whole different discussion.

Finally, all paths are great and will help you to advance in your career. The best fit for you depends very on much on your current background and where you want to get.

Business Analyst Path

If you don’t have any programming or IT knowledge and don’t feel ready or interested learn this kind of skill right away but still want to go deeper into the data world then this is the best path. In this career path, you’ll learn to work with data using low-code or even no-code tools, such as Excel and PowerBI.

You’ll also learn about SQL and how to extract data from databases, which can be the hardest part if you’re not comfortable writing code but I can assure you it’ll be of great value. From my experience working as a data scientist and interacting with business analysts, I can see, on a daily bases, how this skill is important for them and make them stand out from the others.

Data Analyst Path

If you really want to get deep into the data career, you’ll eventually need to write some code and learn at least a bit of a programming language.

If you are already into programming, this path can be a great way to use your abilities for working with data. If you’re not, but feel like taking this new step in your career, this will be a great introduction.

Also, personally, I think you should give a chance to write some code if you have never done it. It’ll bring numerous benefits to your data career.

Data Scientist Path

If you feel comfortable with the Data Analyst path and with programming in general, you could then move on to the Data Scientist path. However, you should expect **more math and statistics-related topics ** on this path. You will be introduced to calculus, algebra, and probability, for instance.

In fact, the Data Analyst path is a part of the Data Scientist path. So you can start off with Data Analyst, and you’ll also be taking around half of the Data Scientist path at the same time.

Data Engineer Path

You don’t need to know to code as a prerequisite for this cath too, but you should be aware that it will lead you to a more IT-related field and it’s not too focused on business.

Just like the Data Scientist path takes you from basic programming to math, statistics, and machine learning, the Data Engineer Path takes you from basic programming to more advanced computer science topics. So be ready for that.

Summary

If we split the data field into four topics: business, databases, programming, math/statistics, and advanced computer science, the following matrix show which of these areas you’ll interact with by taking each career path:

Business Databases Programming Math/Statistics Advanced Computer Science
Business Analyst X X
Data Analyst X X X
Data Scientist X X X X
Data Engineer X X X

About the Data Engineer Path: you’ll also have to understand the business while working as a data engineer. However, from my experience, this understanding is much softer than the others and that’s why I left it blank.

I hope this can help you make up your mind. If you have any questions, I’ll be glad to help.

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Very useful article, thank you for putting it together.
What I found really useful was the table at the end.

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