Joy Onuoha Ebedo

If I had to learn Data Analytics from scratch today, here's exactly what l'd do step by step.

A practical roadmap based on real-world experience:

→ Start with core concepts & tools (Excel, SQL, Python)

→ Build a strong foundation in SQL & Python

→ Learn data visualization (Power BI/Tableau)

→ Work on real projects with real datasets

→ Understand the business behind the data

→ Explore cloud tools like Azure & Databricks

→ Keep learning, building, and connecting with others

The key? Focus on doing, not just learning.

Want to learn more? Don't forget to follow, like, share, and comment.

When you're starting out in data, it's easy to feel lost

Too many roles, too many tools, and too much pressure.

I've been there stuck in a loop of courses and confusion.

But the good news? Feeling lost isn't permanent.

In this post, I shared 5 steps to find your direction in your data career:

📍 Clarify your career goal
📍 Build skills with purpose
📍 Find a mentor or community
📍 Track your progress
📍 Connect your skills to business impact

These steps helped me (and my students) go from lost to focused. They can do the same for you.

What's the biggest challenge you're facing in your data career right now?

Drop it in the comments, let's figure it out together

Feeling buried under Python, SQL, Power
BI, Azure, AWS, Databricks, Docker, Spark?

You're not alone, and more tools isn't always the answer.

The truth?

Stacking tools without a clear plan can actually slow you down.

Here's how to stay focused:

→ Pick one tool per purpose

→ Solve real problems, not just tutorials

→ Go deep, not wide

→ Choose tools based on your career path You don't need every tool.

→ You need the right ones for your next step.

Want clarity?

Comment on your current focus (analyst, engineer, or scientist) and l'll send you 3 tools to prioritise.

From Civil Engineering to Data Science

This is how I made the switch step by step.

I graduated with a First-Class in Civil Engineering, but I knew I wanted more:

More tech. More data. More impact.

I pivoted into Finance & Insurance, where I saw the power of data in action:

Fraud detection, risk modeling, and customer insights.

That experience pushed me to earn my MSc in Data Science & Al from the University of Liverpool.

Since then, l've built ML models, automated pipelines, and led data-driven solutions in real business settings.

Now?

I'm building BricksHub, a practical learning platform helping data professionals go beyond tutorials and become real-world ready.

Thinking of switching careers into data?

Here's what l've learned:

📍 Your past experience is valuable.
📍 Business impact matters more than buzzwords
📍 Real projects will teach you more than any course alone.

👉🏽Enjoyed reading this? Don't forget to leave a comment, share and follow for more

I transitioned from Civil Engineering to Tech…

Started with Excel and reports that barely moved the needle, until I discovered what was possible with automation, ETL data pipelines, and machine learning.

Now, I'm helping other data professionals make that leap too.

Through BricksHub, I teach data the way it actually works in the real world, with more projects, more confidence.

Here, you'll find:

📍 Real end-to-end projects

📍 Cloud, Data & Al lessons that drive business impact

📍 Career tips that go beyond surface-level advice

📍 Behind-the-scenes of building BricksHub from the ground up

For tech switchers, data newbies, and pros who want to grow deeper, not just wider, this is your space.

Let's build, not just learn.