A while back my site was featured on Careerfoundry among “9 of the Best Data Analytics Portfolios on the Web“. Since then, I have been receiving many lovely messages from analytics students who are looking to build their own portfolio, asking for advice and mentorship. I wanted to write a post to collate these questions and answer them in more depth.
Do you need a dedicated site?
You don’t need a dedicated website for your portfolio. I only created mine when I started contracting and wanted to have a succinct and easily accessible place to share my services, showcase my previous work and make myself available for contact. Before this, when I was applying for roles, I simply shared links to my Tableau Public profile and blog. For some of you this will be your GitHub profile. Where this becomes difficult is if your work sits in many different places and you would need to share multiple links for a recruitment manager to review your work. They are less likely to do this. A dedicated site for your portfolio will make your work look more professional and will give you the chance to include other types of content.
How do you build a site?
If you don’t know how to code, I would recommend using a content management system (such as WordPress, Squarespace or Wix) that makes the set up of a website easy for you to do yourself. There are many free templates available that you can easily update with new content yourself whenever you need to. You don’t want to have to rely on someone else to do this. You can pay extra to have your personal domain on these content management systems or to buy the perfect template rather than use a free one, but it’s not necessary. As someone hiring for a data visualisation specialist I wouldn’t care if you have a custom domain. I would however pay attention to the layout and design of the site, since this is a reflection of your design aesthetic.
Who is your audience?
Just like with a data visualisation, one of the first things you need to be clear about is who you are making your portfolio for. Is it to apply to jobs? Do you want to advertise your freelance services? Is it a way to connect with the rest of the community? You might even have different portfolios for different purposes, but make sure your goals are clear and you don’t try to do it all in the same place.
What’s your persona?
A portfolio exists to introduce you and your work. Within the field of analytics and data visualisation there are so many ways to specialise, and this is your chance to communicate to your audience what you are good at and who you are as a person. When hiring someone for a position, you aren’t usually looking for someone who says they can do a little of everything, you are looking for someone who can do the thing you need really well. You might also be looking for someone who fits the values of your organisation.
Think about what you enjoy and what drives you in your work. What are the topics that you are most passionate about? What sets you apart from others that you have worked with? Which projects have you found most fun?
- In my visualisation work I focus on clean design, not complicated technical challenges. That’s what I enjoy doing, so that’s the work I want to be hired for.
- I have experience in survey design and social research through my degree and early career. This sets me apart from others in the field. I make sure to highlight these skills in case this is a speciailty a client is looking for.
- I am committed to work that has a social impact, with a special passion for gender issues and health. Of course, I have worked in corporate contexts and could showcase those skills, but that’s not the work I am looking for, so I don’t highlight it.
How do you make projects?
Especially at the start of your career you might not have any published data visualisations that you can link to. Equally, if you have worked in a business context, your work might not be public, so how do you evidence your experience?
Work projects
If you have built visualisations or an interesting analysis in a work context that can’t be shared publicly, this doesn’t mean that there is no chance for you to include it in your portfolio. You could:
- Take screenshots and make sure to blur out any confidential information
- Replace the data source with mock data and remove any details such as logos, then republish this on your own profile
- Recreate a similar dashboard in your own time with different data
- Write a blog post about what you did and why, perhaps including some sketches that show the dashboard set up (this is also what I do for Alteryx projects)
In all these cases you will want to clear this with your manager or project lead, different companies will have different policies, and some will be stricter about the boundaries of intellectual property than others. It’s a good idea to get into the habit of collecting these examples as you go along, so that they are ready when you need them. Looking back, there are a bunch of projects that I wish I had saved in some way to include in my portfolio now.
Personal projects
If you can’t go any of the paths above to use your professional work, or you are just starting out, personal projects are a great way to gain experience and show your skills.
You can take part in existing data challenges, which will set you a task and usually provide cleaned data.
- https://www.makeovermonday.co.uk/
- https://www.kaggle.com/competitions
- https://www.vizforsocialgood.com/
- https://www.storytellingwithdata.com/swdchallenge
- https://sarahlovesdata.co.uk/tag/ironquest/
These challenges are an easy entry point, as they will usually have the data picked and prepared for you. You can either go through the archives to find a challenge that you are interested in or take part in current challenges, which will get you the most engagement with your content and the best chance to get feedback, including from data visualisation experts. Some people set themselves the goal take part in every new challenge that comes out, which is a great way to build a habit for consistent practice.
Hi everyone, here’s this week’s #MakeoverMonday looking at changes in wildlife populations. I experimented with 2 vizzes and decided to keep both!
Feedback welcome#datafamLink – https://t.co/IdihD5Agxy pic.twitter.com/YhGjCJUb2R
— Chimdi Nwosu (@menscuriosa) May 24, 2021
A step up from this, and I would say the best way to show off your analytics skills and persona, is to come up with your own projects. Working as an analyst is not just about answering questions that others have asked you, it’s also about your own process of exploration.
To create a personal project:
- Think about something that you are curious about, perhaps a claim that you have heard in the media, or a topic your friends have discussed
- Consider how you could answer this question with data, and see if you can find relevant data or collect it yourself
- Prepare the data for analysis
- Explore the data, discover insights, and visualise them for your audience
Often the steps will be in a slightly different order, where you discover an interesting data set that you then explore to find insights. This is absolutely fine, and another task you will encounter frequently in a work context, where you will be given data and need to discover insights without a clear question statement.
How do I find data?
This question comes up a lot, and the answer is often as simple as a Google search for the topic you are looking for and including keywords such as ‘data’ or ‘csv’. I can also recommend the following resources for interesting data collections:
- https://www.kaggle.com/datasets
- https://www.data-is-plural.com/
- https://data.worldbank.org/
- https://data.world/
- https://github.com/awesomedata/awesome-public-datasets
If the data set is not readily available in a downloadable file, you might still be able to find it elsewhere in an unstructured format
What projects should you feature?
How to get help
Another thing I get asked frequently is to provide feedback on visualisations. It’s important to collect feedback on your work and get used to the experience of hearing this (sometimes negative) feedback and how to use it effectively. You might for instance get opposite opinions on the same piece of work, and you need to figure out what to do with that.
The best place to start can be family and friends. If your data visualisation is meant to be understood by a non-data audience, try it on them. The next step is to put the visualisation out for broad feedback on social media. I recommend Twitter for this. I know this might feel scary at first, but it’s a very helpful process. Try to build up a community and identify the right hashtags to use so that you are reaching the right people. The Tableau community is very kind and supportive. Actively mention that you are looking for feedback. This is important, as many people will not give unsolicited feedback since it is often not welcome. Make improvements to your viz and post it again. This shows people that you really care about their input, and they are not wasting their time. People will be very happy to provide support in this way and it will help you put together a great portfolio. If you ever struggling for responses, feel free to tag me (@LediHolly) in your Tweet and I will make sure to respond.