Hey there!

I've been getting a lot of messages lately about my old Tableau practice sets (you know, the Superstore ones).

The feedback has been consistently positive, but there's also been a pattern:

"These were great for learning the mechanics, but my real work data is... messier."

This got me thinking. A lot.

The Problem with Perfect Practice

Most Tableau training (including my own previous work ... hello Superstore data set!) uses sanitized datasets.

• Everything adds up perfectly.
• No missing values.
• No weird anomalies.

And the exercises are like:
​"Create a bar chart showing sales by region."

But that's not real life, is it?

Real life is your manager dropping by at 9 AM saying
​"Can you quickly show me which products drove our revenue last quarter? I have a call with the product team at 10:30."

Real life is figuring out what "quickly" means, what level of detail they need, and whether those negative sales amounts are errors or returns - all while the clock is ticking.

I'm "Renovating" ... Here's What I'm Building Instead

I'm completely rethinking how I approach data training education.

Not just the technical skills, but the analytical thinking that makes you someone people trust with important questions.

I'm starting with a free 5-day email course - realistic workplace scenarios, messy data, and critical thinking skills. This focuses on Tableau foundations/fundamentals but the learnings will go way beyond any single tool.

This will be especially valuable if you're:

• Starting a new role and want to handle data requests confidently from day one
• Switching industries and need to understand how different businesses use data
• Preparing for interviews where they'll ask about your analytical process
• Want to demonstrate practical problem-solving skills, not just technical knowledge

Sneak Peek: What This Can Look Like

Here's Day 1:

It's Monday morning, 9 AM. You're settling in with your coffee when your manager stops by your desk.

Manager: "Hey, quick question. Can you show me which products drove our revenue last quarter? I have a call with the product team at 10:30 and need to know where we're winning."

Your mission: Use Tableau to clearly answer this business question - but first you need to interpret what they actually need.

What you'll discover: Some negative sales amounts in the data (returns? data errors?), inconsistent product naming, and the difference between showing what they asked for vs. what they probably need.

Time: 15 minutes (because that's how long you actually have)

Notice the difference?

You're not just learning Tableau mechanics.

You're learning to think under pressure, decode unclear requests, and provide reliable insights when it matters.

These analytical and communication skills transfer to any tool, any role, any industry.

Why This Matters Now

In the age of AI, basic chart-making is becoming commoditized. What's increasingly valuable is the judgment to interpret unclear requests, know when to trust data vs. dig deeper, and present findings with appropriate confidence.

I'm honest - this is still a work in progress. I'm experimenting, testing scenarios with real professionals, and refining based on what actually helps people in their jobs.

But I'm excited about where this is heading. Instead of teaching you to be really good with perfect data, I want to help you be confident with messy, realistic, workplace complexity.

What do you think? What workplace data scenarios make you nervous? What would you want to see included in this foundational course?

Hit reply and let me know. Your feedback often becomes the seed for the next breakthrough.

Chat soon,
Donabel

P.S. If you've worked through my previous practice sets, thank you for the feedback that's helping shape this new direction.

If you haven't seen the previous Tableau Practice Sets - they're here:
​https://sqlbelle.gumroad.com/​

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