Important things to know
This is the complete guide to building your data analyst portfolio ahead of your job applications for a data analyst role in 2024 and beyond.
Your data analyst portfolio is your opportunity to demonstrate your skills while crafting a unique story to sell your skills. However, these stories are not mere tales but a professional one filled with facts about your data analyst experiences.
This article provides a complete guide to creating your data analyst portfolio
But let’s try to define a data analyst portfolio:
“A data analyst portfolio is typically a link destination (single or multi-paged website or platform section) that showcases your best skills and projects executed to your potential employers and hiring managers.”
Now, let’s dive right into the guide.
Essential Elements to Include In Your Portfolio
Blogs have outlines and websites/design projects have wireframes. Similarly, your portfolio requires a basic outline of what you’ll be adding in the portfolio document or website page. The essential elements that form the outline will eventually form the body of the portfolio. These elements are outlined below:
About me
Your about me section gives you an opportunity to connect with potential employers and hiring managers on a personal level. You’ll be introducing yourself to everyone who lands on your portfolio page. The section can include the following:
- ✅︎ Your name
- ✅︎ Academic background
- ✅︎ Your journey into data analysis
- ✅︎ Your biggest interests in data analysis
- ✅︎ Links to your social media accounts and contact details
Past Projects and Case Studies
Projects form the bulk of a data analyst portfolio. These projects will help you prove your best skills with past project case studies (paid or unpaid). Your portfolio projects should be in descending order showing your best and latest projects at the top and your most basic and oldest projects at the page bottom. Your portfolio projects should highlight the following:
- ✅︎ How you scraped data from various websites including your code and comments to explain your thought process.
- ✅︎ How you cleaned a data set containing data with some issues. Walk portfolio reviewers through your processes.
- ✅︎ How you carry out different types of analysis including diagnostic, descriptive, predictive, and prescriptive analysis.
- ✅︎ Showcase how you visualised insights from a data analysis to tell a story with a chart, map, or graph.
- ✅︎ Highlight projects where you collaborated with another team to execute.
Skills To Prioritise Showcasing In Your Portfolio
The skills to prioritise in your portfolio is a major point of discussion because they will form the backbone of how you will structure your portfolio. Otherwise, you may run a risk of not adequately making a strong case in your portfolio. You require a perfect mix of technical and soft skills to be in the top 1% of most marketable data analysts. The following are the skills to prioritise showcasing in your portfolio:
SQL
SQL or Structured Query Language is the most frequently used language to communicate with databases. SQL enables you to structure and alter data. You can query, modify, and organise data contained in relational databases known as schema). A proficient understanding of SQL is the most basic and important skill for you ahead of landing a data analyst role.
Maths, Probability, and Statistics
You might be a little scared on this note if you are generally not a fan of mathematics. However, even though much of the work in data analytics is well automated with tools you still require a basic understanding of maths, probability, and statistics to establish your ability to function in a data analyst role. Regardless of the affinity of maths, probability, and statistics with individuals with science backgrounds, it doesn’t stop arts majors with an established interest in data analysis from not brushing up on these topics and applying them as is necessary.
Programming Languages
Programming is a huge part of data analysis. Programming languages, such as R or Python, are the tools that data analysts use to execute complex data analysis with the input of some commands. The open-source nature of both R and Python allow you to work with them prior to application and add them to your portfolio. Having either R or Python on your portfolio will give you an edge in your applications and portfolio reviews.
Data Visualization
All the earlier discussed skills will help you draw useful insights from data but creating a clear visualisation of the data is important. Visualisation involves using these insights in a more useful way that requires the ability to help non-professionals have an understanding of what the data states and help them make better decisions. Some of the ways you can visualise your data includes the use of charts, graphs, and animations. A major visualisation tool to learn is Tableau which allows you to create dashboards and business intelligence reports.
Critical Thinking
Critical thinking is a soft skill that you can learn and prove in your portfolio. It is the practice of carefully studying a situation, weighing the available options, detailing the workable solutions, and applying the most suitable to the situation. You can prove your critical thinking skills by doing the following:
- ✅︎ Outline the issues you identified on a project.
- ✅︎ List your findings after a further investigation into the identified problems.
- ✅︎ Detail your solutions you applied in the project.
Best Platforms to Host Your Portfolio
You also need to choose where to upload or host your data analytics portfolio. Most platforms offer a free option to host your portfolio as quickly as possible. Leaving only data analysts who need a high level of customisation to pay for a premium version. Here are some of the best platforms for you to consider hosting your portfolio:
GitHub
GitHub, an open-source community of over 50 million developers, is one of the best platforms to upload your portfolio projects. On the platform you will not be uploading your project but can get useful project contributions that will help you make helpful changes to the work you have done. Recruiters love GitHub because it means your project isn’t exclusive to you but also available to other developers to review showing a level of confidence in the work you have done. Using GitHub also opens you to a large community that allows more people to access your work. The process for using GitHub to host your portfolio is as follows:
- ✅︎ Create an account.
- ✅︎ Choose the elements you want to show off including codes and Jupyter Notebooks.
- ✅︎ Start adding data projects to a public repository.
LinkedIn is not an exclusive community to developers but it makes it very easy to add and update data projects from your profile. This allows you to use your LinkedIn profile as an online portfolio. LinkedIn supports formats including .jpeg, PowerPoint, PDF, Docs, and videos. The featured posts section of the platform is one of the best tools to make it easy for recruiters to find your portfolio.
Another trick many data professionals use is to add a link to their GitHub projects from LinkedIn creating a double-edged portfolio for themselves.
Kaggle
Kaggle is a customisable cloud environment for Jupyter Notebooks that allows you to upload your portfolio for free. You can upload results of any native Kaggle competitions you have engaged in and program codes you wrote from scratch.
Improving your portfolio’s visibility in Kaggle includes:
- ✅︎ Experiment with Python and R programming on more data sets available on the platform.
- ✅︎ Upload your data sets and coding notebooks for a larger audience to view them.
- ✅︎ Use relevant hashtags to increase the visibility of your datasets and notebooks.
The more people who view and vote on your work, the better your Kaggle rankings. Therefore ensure your projects are designated as public to earn more upvotes.
Build your Data Analyst Portfolio with Amdari
You already know that the easiest way to land that data analytics role is to showcase your skills in the most mouthwatering way possible for potential recruiters to agree with your level of expertise. Data analytics projects will additionally help improve your experiences with data analytics.
You can access an impressive suite of data analytics on Amdari. Here you will find many great and tasking real world projects that will help you upskill and quickly get to building your portfolio as quickly as possible.
You can also read: 15+ Data Analyst Projects for Beginners and Experts
FAQs
What do I put in my portfolio if I don’t have work experience?
Visit the Amdari platform today to choose a project to work on as quickly as you can. We can guarantee you will be working on projects with real world applications.
Why Do I Need A Data Analyst Portfolio?
Your portfolio helps you to display your skills and how they apply to work in the real world.
What Should Anyone Reviewing My Portfolio Find?
People reviewing your portfolio must be able to know a little bit about you, your skills, and the projects you've worked on.
