TDP #12: Creating a Well Laid Out Data Portfolio

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I always recommend that every data analyst have a project portfolio, whether you’re aspiring to be one or already in the field.

Having a portfolio is one of the best ways to demonstrate your capabilities.

They allow us to go beyond simply saying we can do x-y-z. A portfolio helps us to prove it.

Here are some recommendations for creating a portfolio that’ll turn some heads.

1 | Have one

I know, I know. This one’s not really a “how-to,” but it needs to be said.

I talk to many people who are searching for data jobs that don’t even have a portfolio.

So my first piece of advice: Have one.

Even if it’s not totally amazing at the start, having one is better than not having one. They still provide a visual of your skillset and they show the effort you’ve put in to go above and beyond.

2 | Choose an easy-to-use platform

There are two in particular that I suggest.

The 1st is Carrd.

Carrd is absolutely amazing. It’s easy to use, highly customizable, and best of all, it’s FREE. You do get a few more benefits with their paid plan, like embedding videos, but it’s only $20 a year. Not a month, a YEAR. It’s honestly a steal.

It’s a landing page builder and it’s very smooth.

This tool is great for those with a creative eye who want to put the work into creating a page that is unique and eye-catching.

I personally use Carrd and love it. Check it out here.

My 2nd option is the Maven Analytics Showcase.

Maven is an incredible platform. It’s one of the best places to go to learn data skills.

They also have their Showcase feature which is essentially a portfolio.

This is a great option for those looking to get their portfolio off the ground quickly. It’s a hard-coded platform meaning there isn’t much room for customization, but it’s very well laid out. This allows people to get set up fast.

Check out Maven Showcase here.

3 | Take the 1 project per skill approach

Each tool you know how to use should be represented with at least one project.

An example setup might look like this:

• 1 SQL project

• 1 Tableau project

• 1 Power BI project

• 1 Python project

This ensures that each of your skills is represented with at least one demonstration specific to that tool.

It’s ok to overlap some of these too. For example, your Power BI project could also demonstrate data cleaning in SQL.

You can have a dedicated SQL project, but then also a Power BI AND SQL project combined.

I think 1 project per skill is a pretty clean approach and easy for those viewing your portfolio to follow.

4| Pick your best and brightest projects

Avoid the temptation to overload your portfolio.

This is especially true if you’re taking the landing page approach with Carrd.

Represent your BEST projects on your landing page with an image, a short description, and a list of functions used to make the project.

If you have Carrd pro you can also show video walkthroughs through tools like Loom (highly recommend).

Then link your Github and Tableau Public to your landing page so people can view everything else if they want to.

5 | Show off your portfolio

Portfolios are great but not if nobody can see them.

Here are a few places you be linking your portfolio:

• LinkedIn info section (at the top of your profile under your profile pic)

• LinkedIn featured section

• Your resume

• Every job application that gives you the option

• In a LinkedIn post every now and then

Get the word out to draw eyes to your work. Make it easy for recruiters and employers to find it.

Take these tips and go create a knockout portfolio.

That’s in for this week friends.

See you next time ✌️

Whenever you’re ready, here are 2 ways I can help you:

1 | The Data Portfolio Guidebook

If you’re looking to create a data portfolio but aren’t sure where to start, I’d recommend this ebook: Learn how to think like an analyst, develop a portfolio and LinkedIn profile, and tackle the job hunt.

Join 450+ learners here.

2 | 1:1 Coaching Call

For help navigating the data job hunt, consider booking a 1:1 career guidance session with me. We’ll review your resume, portfolio, and LinkedIn, and we’ll also develop a roadmap to get you to your ideal data job faster.

Schedule a 1:1 here.