data analysis projects

How to build a portfolio of data analysis projects

Why is it so important to build a portfolio of data analysis projects (on the side) when you want to transition into data analysis? And how can you find worthwhile projects to focus on?


  • Build a portfolio of data analysis projects to practice your data analysis skills on the job
  • Use them to show off your experience and excel in interviews
  • Focus on projects that provide actual business value and impact
  • If you can’t find any projects either do a course which provides use case or think about getting another position where more data is available

One thing I see recommended again and again when someone wants to transition into data analysis (and doesn’t have any analytical experience so far) is to look for opportunities in whatever job you have right now and start doing data analysis work here and there. Build a portfolio of analytical or data analysis projects (on the side).

And I highly agree!

Having a portfolio of data projects is one of the best things you can do to take a first step towards the transition into data analytics and will make the interviewing process a lot easier. You will learn some data analysis skills along the way and you’ll have something to show for experience.

However, having analytical side projects is often easier said than done and a couple of questions naturally come up: 

  • What kind of projects should you focus on?
  • How do you find (side) projects?
  • What should you do if you can’t find any viable projects at your current job at all?

Would it be great to have clear instructions on which projects to focus on without wasting time and how to find them?

That’s exactly what’s below post is about!

Why having a portfolio of data analysis projects is so important

Having a portfolio of side projects will help you to build experience when it comes to data analysis and serves primary two purposes: 

Building data analysis skills

Learning the right skills for data analysis is a chapter on its own. However, learning them by taking courses, reading books, or consuming any other learning resources is only half the battle. Equally important is applying those skills, e.g. in side projects. Only by applying them will you know how to use them on the job and not in a “perfect” environment with clean data such as in course exercises. That’s where you learn the fine details of how to deal with the hiccups every data analysis project will have.


Building a portfolio of data analysis side projects will give you something tangible that you can use to show off your data analysis experiences. Out of personal experience: Having a portfolio of projects helped me tremendously when I applied for an analyst position. It will make all interviewing stages a lot easier. It will help you to get through the first screening stage which is usually conducted by HR by having those projects on your CV and showing that you already have some relevant experiences. And they will help you during the interviews themselves as you can talk about those projects and give in-depth examples to STAR interview questions on what you did in the past.

What kind of data analysis projects to focus on

Finding the right projects to focus on probably one of the biggest challenges for those who want to transition into data analysis. Two tips on where to find worthwhile projects:

Focus on projects that provide business value

Don’t try to analyze random data for its own sake. You will lose motivation very quickly and will rather “play around” with the data without drawing any learnings or insights from it. Instead, use a data analysis framework to define clear business challenges you want to solve with data. It gives you a clear path on what to do while making sure your analysis will actually provide business value.

And again: This will help you with interviewing by being able to show that you had actual impact with your data analysis skills in the past. Vanishingly few aspiring or existing analysts realize the importance of providing business value and impact and try to compete on technical ability when no one really cares.

Where to look for projects

So this is something that many are struggling with as they believe there aren’t any good projects to pursue in their current job. The truth is most companies and teams will have at least some challenges that can be solved with data. The above mentioned framework is a good way to find those challenges. It helps you define the business questions first and only then look into what data and analysis can help to solve them.

Too many make the mistake to start with data and get lost in it. They look at the data first and try to find all the cool analytical methods they can apply without having a clear business outcome in mind. Usually ultimately leading to nothing and giving up as they don’t know what to do (a.k.a. “I don’t have any potential data analysis projects worth following”).

So look for small projects in your job that will help you solve some of your challenges. And if you can’t find something in your immediate tasks or team: Find something that annoys your manager or director or the leader over in sales that you know. I guarantee you they have some data pain points and you could solve it for them as a starter project.

What to do if you really really can’t find any data analysis projects

So let’s say you really can’t find any data analysis projects you can take on. For example. because your current job or company doesn’t deal with any data or the core business is very far away from your dream data analysis job (e.g. you work in a theater but want to transition into marketing analytics). Or even worse: Your boss/company doesn’t allow you to follow any data analysis side projects. You still have two options on how to find projects:

Option 1: Take a course that lets you work on real-life use cases

When choosing a course for learning data analysis make sure to choose one where you’ll work on real-life use cases from the domain you want to work in. I.e. avoid courses where you’ll study statistics, etc. for their own sake or where you work on generalized challenges such as supply chain management while you want to work in online marketing. 

For example Data Analysis for Marketers is a resource for learning data analysis specifically for digital marketing. As such all the projects you work through are real-life use cases you can use on the job.

By taking a course where you work on relevant projects it will make it a lot easier for you to transfer the skills you learn there to something on the job. It might help you to identify possible projects to work on after all. 

And if you still can’t find any projects: You are actually building a portfolio already by simply taking the course and working on the course projects! If you have chosen a course that has use cases from the domain you want to work in you will build a portfolio of relevant data analysis projects that you can use to show off your skills.

Option 2: Take an intermediate step

If you can’t find any relevant projects in your current job at all it can be a good option to take an intermediate step closer to the data analysis job you want, i.e. take another job that is closer to the domain you want to work in.

Let’s take the example from above again: You are working as a set designer in a theater and want to work in data analysis in digital marketing. You could either apply internally for another job such as social media manager for the theater or you could look externally for a more generalized job in digital marketing which usually has lower entry barriers compared to something specialized such as data analysis. Both would bring you closer to your real goal of working in data analytics and both jobs will have a lot more data available which you can use to build your data analysis project portfolio.