tgroenwals shared this post · Apr 21

The biggest myth in data teams is that data workflow is a straight line.

Data → Model → Insight → Decision

That’s not how real systems work, it only looks like that on slides.

But in reality, nothing is linear.

Before you even get to insights, you’re already stuck in definitions, broken data sources, conflicting metrics, and teams that don’t agree on what “truth” means.

Then comes modeling, where assumptions change mid-way.

Then governance, access, and compliance slow everything down.

And even after launch, adoption fails if the business wasn’t aligned on the problem from the start.

Rakesh Khanduja The biggest bottleneck in data isn’t analytics — it’s the messy loop between definitions, trust, ownership, and adoption.

The teams that win stop managing data as a pipeline and start managing it as an operating system. Apr 20 1 like

Yassine Sakkaf The part about definitions and truth hits hardest. Most delays don’t come from modeling, they come from misalignment before the work even starts, KOMAL. Apr 20 1 like

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