How to Build Effective and Attractive Portfolio for Data Analyst in 2024
Hey! If you are here, then you are looking for new career opportunities, enthusiastic about getting a new position, or learning new skills. It's commendable and I respect it. The career of a data analyst for me is the most attractive in IT. I've been working with data all my life because numbers never lie.
I got a career as a data analyst relatively recently, I went to this goal for a long time, trained, learned new skills (I even had to learn math), and, of course, built my portfolio. Unfortunately, I can’t show you my portfolio, but I will definitely show you some of my notebooks from Kaggle at the very end so that you have an idea of what I’m talking about.
Why do You Need a Portfolio at all?
Now you will not surprise anyone with your unique resume with an unusual design - this is the default PDF page that everyone has, it is of no interest to anyone and no one cares what is written there - rest assured. Everyone is only interested in what you really know how to do - write scripts for cleaning datasets, visualize data, conduct EDA, and so on. This is your main value.
Your Portfolio Feedback - rwebdev Thread (source)
These skills must be shown. For example, one of my good friends from the university chose YouTube streams as a portfolio, where he periodically broadcasts, where he writes JS scripts for his projects (he is a frontend developer). A very creative approach that does not suit everyone, but stands out from other formats. It is not necessary to reinvent the wheel, and you can stop at something more or less classic - for example, a portfolio.
In general, I personally support that everyone, at least in the IT field, has their own portfolio, no matter if you are a support specialist or a technical writer. You should have real examples of your work that you are not ashamed to show, that make you proud, or at least not cringe.
What Should Be in Your Portfolio
A very simple question and here is my simple answer - whatever you see fit. If I were doing my portfolio now, I would stick to the following plan and include the following items in my portfolio:
- Data cleaning (data manipulation on pandas) is a must if you are starting a career in data analytics from scratch and have zero experience.
- Data Visualization - There are so many ways to visualize data. For some it's Excel, for some, it's Matplotlib, for some, it's seaborn (as, for example, for me). Anything, the main thing is to show that with the existing dataset, you can do something, do something useful.
- Business conclusions - Building graphs and processing the dataset is only 50% of the work. You must show that you understand what you are doing and why you are doing it. You must first ask yourself what you want to get from this data, and only then build a graph and visualizations. Not vice versa.
Perhaps this is the most important thing. I build my portfolio exactly according to this plan because the steps I have listed are in fact 80% of the work of each data analyst and showing mastery of these skills means bringing yourself closer to your cherished career, showing the employer that onboarding for you can be reduced by 5 times, because you already know a lot of things.
Sandbox is Better than PDF
A lot of people present the results of their work in the usual PDF format, on a regular sheet of paper. Of course, you can do this - this is how designers and architects work, but it's not designers or architects who gathered here, but IT experts who want to start a new career and attract recruiters. I would recommend you a sandbox.
Free Portfolio Generators - Canva. If you've chosen PDF version (source)
A personal site is also not a bad idea, but it still requires some basic skills and knowledge in web development (even the most minimal, but it requires). If there is no such knowledge, then it's okay - there are sandboxes that seemed to be created for people who do not want to scatter their strength and energy on everything but concentrate on portfolio.
Sandboxes are different and there are a lot of them. For data analysts, I highly recommend Kaggle. This is a huge sandbox for data scientists, where there are a huge number of open and accessible datasets with the ability to create notebooks for them. I will talk about Kaggle in the next paragraph, but here I will only note that these notebooks and your profile in this sandbox will be your portfolio because all data specialists are very familiar with this platform.
I Advise You Kaggle
On our site, a huge amount of material is devoted to Kaggle and this is not just. First, it is an excellent and free resource for data education. This is the place every data analyst should be aware of, bar none. Secondly, which is an important point for us, this is an excellent site where we can build our portfolio. In fact, simply maintaining your profile is what we consider a portfolio.
Kaggle Courses (source)
From numerous datasets, each user can create their own notebooks, conduct their own research, look at the same data differently, share experiences, comment on someone else's code, and ask other users if some material is not clear and help is needed (here they will always answer and always help).
If you actively maintain a profile here, recruiters will come to you. For certain achievements, you get titles and medals, just like in any other sandbox. Based on these attributes, you rank in the leaderboard, thus attracting more attention if your code is worth it, of course. I highly recommend keeping up your account here - it's convenient and, most importantly, accessible to everyone.
Examples From my Portfolio
I thought it would be strange to share my experience with you and not provide examples of personal notebooks. I have selected some interesting notebooks from my profile. The first one, for example, is about my work with scatter plots and plotting with correlation. This was my practice notebook, but I decided to make it part of my portfolio, why not:
Here is another example of how I arrange my portfolio. Here I practiced working with latitude and longitude, maps, and geography in general, projecting data onto a map. By the way, here I also trained in writing parsing scripts, and collected data using Python and the official website of the company, which was doubly useful for me:
Conclusion
So, I hope I inspired you to create and maintain your portfolio. This is extremely important now when the IT market is simply insanely competitive. It is necessary to somehow be different from others, to invent something in order to attract attention and be brighter (professionally) than others. Of course, my laptops are not the limit of perfection, I realize this, in this case, creating a portfolio is a whole art. It would be very interesting for me to look at your portfolio. Be sure to create a thread on our Reddit if you like. It will be interesting to take a look at them.