Your first data analytics project in a weekend

Skip the overwhelm, here’s how to start small, showcase your skills, and land that first opportunity

Photo by Luke Chesser on Unsplash

👋🏽 Hey, it’s Ismail. Welcome to data nomads lab newsletter on learning data analytics, career growth, networking, building portfolios, and interview skills to break into tech role as a high-performer.

Want to break into data analytics without a degree?

Here is how to create your first project this weekend.

Here is an uncomfortable truth: I used to think building a portfolio-worthy analytics project was complicated. Advanced coding, fancy visualizations, expensive software.

I was wrong.

Let me tell you about one of my students.

This student had been learning analytics for months, dabbling in Excel and Tableau, but felt stuck. Like many beginners, they thought creating a portfolio project would take weeks.

Just like many of you noticed, the same question kept popping up in LinkedIn posts:

How do I get started analyzing real-world data sets?

Instead of reading another tutorial or watching another video, they took action. On Saturday morning, hey downloaded a free Kaggle e-commerce dataset. That afternoon, they analyzed trends and built three simple Tableau dashboards showing sales, customer behavior, and product performance.

By Sunday night, they had:

• A clean, insightful dataset

• Three polished dashboards

• A one-page write-up explaining their process

The results?

They shared everything on LinkedIn and Github. Within a week, they connected with recruiters and a hiring manager. While not a job offer, it was progress.

It really can be that simple to get started.

The beginner portfolio method

Here is the framework this student used (and why it works so well):

1. Find ONE simple, real-world dataset

2. Analyze ONE specific question or theme

3. Create ONE polished visualization (or a few)

4. Write ONE short explanation of your findings

Here is the thing: most beginners overthink this. They try to tackle massive projects that cover everything, but in reality, your future employers do not want everything, they want to see how you approach problems.

Focus on solving one specific problem with your project.

Resources to jumpstart your first project

Here are some excellent resources to get started with data analytics and visualization.

• Data Analytics by Quantium:
  Explore the power of data and its ability to power breakthrough possibilities for individuals, organizations, and societies.

• Data Analytics & Visualization by Accenture:
  Apply your data analytics and visualization skills to advise a social media client on their content creation strategy.

• Power BI by PwC in Switzerland:
  Use Power BI to clean, wrangle, and visualize data to help a telecom client better understand their customers and employees.

• Data Visualization: Empowering Business with Effective Insights by TATA:
  Learn how to create impactful visualizations around important business questions and present findings to executives.

• E-Commerce Dataset on Kaggle:
  This fictional e-commerce dataset is perfect for practicing data analysis, visualization, and predictive modeling.

Quick win for today: Explore these business questions

If you are using the Kaggle e-commerce dataset, try answering some of these questions:

• What are the most popular product categories based on transaction volume?

• What is the average transaction amount across all purchases?

• How does the average product price vary across different categories?

• What is the distribution of discounts offered in transactions?

Spend a couple of hours exploring a dataset, build a simple dashboard or analysis, and share what you learned.

Questions 1 & 4 answers (plots) are below

Did this post help you feel more confident about starting your first data project? Share your thoughts in the comments. Which of these resources are you most excited to try?

If this newsletter inspired you, share it with someone who is starting their data journey. Your support helps me keep writing and creating helpful content for aspiring data professionals. Let us grow together!