If you’re applying for a first Data Analyst role and have no work experience at all, then it’s very likely you’ll need to create a portfolio to develop and demonstrate your analytical skills. It’s not impossible to land a job without one, but having a good one will improve your chances significantly (that seems to be the general consensus and I think it’s probably correct).
It can be tough to know where to start or what projects to develop. You don’t want to waste your time developing something that isn’t effective at landing you a job, either because the portfolio doesn’t demonstrate relevant skills or the projects are very far off base what your potential employers are looking for.
When you’re developing your portfolio, it should ideally do a few things:
- It must help you actually practise data analysis. The more projects you can do, the better you’ll get and if you are in the fortunate position to be able to develop lots of projects, then you can afford to start revising your early attempts and make them even better.
- It’ll help you feel more confident when you are interviewing, especially if your projects touch on aspects of the roles you’re applying for.
- You develop the skills most relevant to your future first role.
An additional benefit is that you will become more data literate as your practice, so even if you end up taking an interim role while continuing your job hunt, you might find that you can leverage that interim role to start incorporating data analysis into it – further accelerating your skill development and perhaps making it easier to switch to an above-entry level role.
With this mindset in place, how can you optimise your time spent developing these skills?
Pick your target industry
My suggestion is to first pick an industry in one of two ways:
- One where you already have an area of interest or are really passionate about. Maybe you’ve always liked Sports Analytics, Healthcare, Marketing or something else, or;
- Pick one where most of the jobs seem to be and you feel at least neutral towards it. When you’re job searching, take notes of which industry keeps coming up as hiring data analysts. In the case of the Netherlands, these seem to be Banking, Utilities and Ecommerce at the moment. All of these are always hiring for all levels. I think you should at least feel neutral towards the industry, because I feel it could stunt your future growth if you aren’t keen on the work.
By the way, you aren’t forever bound to which one you pick. You are free to choose another, but you’ll start off with the cards stacked in your favour and hopefully the first try works out.
Analyse the job ads
Now that you have a target industry in mind, continue looking at the job ads (both active and expired) and start capturing notes on them. Pen and paper is fine but a google doc that you can later refer to is probably more convenient. Make one main list for this and just keep adding to it every time you look at an ad:
What skills are they looking for? Every time they mention SQL, Power BI etc add a checkmark next to it.
What tasks are they describing? Pick out the key descriptions (usually listed as bullet points of activities) and start figuring out what the pattern is across them. Try group them into themes or clusters. Even if you don’t know what these are, write them down anyway. You might later learn enough that helps you understand what these tasks are.
How do they describe their company and the problems they’re trying to solve?
Outline your possible projects that optimise for this industry’s profile
With your list of skills in hand, you should be able to see what tools and software to steer towards. 90% of the job ads mention PowerBI and not Tableau, then it makes sense to use PowerBI instead of Tableau.
With the tasks grouped and counted, you can focus on projects that demonstrate those that seem to come up the most. If they mention a lot of particular analytical methods, or data cleaning, or geospatial work, or web scraping – then work those into your portfolio wherever possible.
With the problems or goals they’ve described, these can be great sources of what business questions to centre your analyses around. Do they talk a lot about customer acquisition? Then do some more research around the problems of customer acquisition and let that form the basis of your analyses.
Search for your datasets
Now that you’ve got a good idea of the industry and their problems, search for datasets (or create them if possible) that get you close to being able to develop projects that attempt to answer them. If you can’t find exactly what you’re looking for (which is very likely), then expand the scope of datasets you can find or alter the possible questions to be able to use what you have found.
This should help you be much more motivated to build a portfolio if it feels like you’re building towards skills you’ll use on Day 1 of the job. Let me know how it goes!
Here’s some related articles you might like:
Manage your data projects like a pro with a free copy of my ebook!
Newsletter subscribers get a free copy of Project Management Fundamentals for Data Analysts worth $12, and I’ll occasionally email you about new blog posts or data-related products I make. Unsubscribe at any time.