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The 48 recurring mistakes in the Data Design Process

Mar 31, 2026
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Late issue
 but still more timely than most dashboards.

For 12 years, I’ve worked with data teams across all kinds of companies.

Different industries. Different stacks.

Same problem.
A lack of method.

Power BI or Tableau.
AI or dataviz.

It doesn’t change anything.

That’s why I built a data design process, inspired by the Double Diamond, adapted to one thing:
Designing data solutions that actually get used

Most teams already feel they need structure.

But even with that awareness, I keep seeing the same mistakes, again and again, in coaching and mentoring sessions.

Not technical mistakes.
Methodological ones.

I’ve documented 48 of them.

No ranking.
Just the reality of how data work breaks in practice.

Fixing these is not a side topic.
It’s the core of my work as a coach and trainer.

Because better tools don’t fix broken thinking.
Better process does.

If you’re dealing with too many requests, too many dashboards, and not enough impact, we should talk.

Book a call. I’ll start by understanding your context and tell you directly if your problem is methodological or not.

If it is, I’ll show you where to focus. If not, I’ll tell you that too.

 Book a call with me here

Have a great week!

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