4 Tips to Create a Solid Project Write-Up

Hey everyone 👋

Welcome to the new newsletter!

If you missed last week’s post, I just transitioned away from Substack to a new platform: Beehiiv, (see that post here).

I also became a LinkedIn Top Voice in Data Analysis this week. Yay!

But enough about that.

This week, let’s talk about project write-ups.

Let me start by saying this: projects are essential to the data job hunt in today’s market.

This is especially true for those seeking entry-level roles.

A good project can really set you apart from the competition. In coaching others, I view lots of projects. Over time, from viewing others and by personal experience, I’ve learned what makes a good one.

And one thing that makes a good project, is a good project write-up.

Here are 4 things to keep in mind for a solid project write-up.

1 | Embrace brevity

The #1 problem I see with some write ups is big walls of text. Either that or a 30 page document that put me to sleep on page 2.

I know you probably worked hard on it, but NO ONE is going to read all of that.

When you consider that the average time spent reviewing a resume is 15 seconds, what hope do you have of someone spending 10 minutes reading through a single project?

Let me tell you, there is 0 chance.

Utilize good copywriting by making text simple, effective, and to the point.

Walk people through the project bit by bit with thoughtful wording. Don’t give them an essay to read.

2 | Have a clear objective for the analysis

Avoid spitting out random insights in your project. This is true for the project itself, not just the write-up.

Rather, identify something specific you want to find out from your analysis and center the whole project around that topic.

This creates a narrative for the project, but it also gives you direction.

Here are 2 ways to do this:

1. After picking your data set, write down a list of questions you have about the data.

   • Then, go about answering those questions while creating the project.

   • Once you have all questions answered, pick a few to include in the final project. Yes, this requires editing and not showing 100% of your work, but trust me, keeping the project clear will work in your favor.

2. Do a general analysis and pick a few conclusions at the end that you want to stick with. Frame questions around those answers to start the write-up with and answer those questions as you go through it.

To recap, we’re picking a set of questions to answer in the introduction of our write-up and answer those as we walk people through the project. Then provide a conclusion to wrap up the project at the end.

3 | Walk people through your thought process

The goal here is to demonstrate your critical thinking and problem-solving abilities.

Let people get in your head as you explain how you went about writing your code or creating your visual.

This is a great way to walk people through the project step by step.

4 | Include a healthy dose of screenshots.

This may go without saying, but I wanted to add it. However, try to do this tastefully.

Think of your-write up like a picture book. You want to hold reader attention with visuals every step of the way.

Don’t leave people reading for too long without a visual. If you do leave them hanging, then it starts to become an essay.

Strike this balance: a little bit of text, screenshot, a little bit of text, screenshot. So on and so forth!

That’s it for this week.

See you next time ✌️ 

Whenever you’re ready, there 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.

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2 | 1:1 Coaching Call

For help navigating the data job hunt, consider booking a 1:1 career guidance session with me. There are a few options available to help you get to your ideal data job faster.

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