Is Your Data Platform Really Built for Success? 🛠️ Here’s How to Tell

Art by @basilonmypizza: https://lnkd.in/eF8FkWzN - https://basilhefti.ch/

Every now and then, I'm asked to review a data platform or data organization. These reviews can feel frustrating. Or become real opportunities for growth.

✅ Objective criteria matter:
- Technology choices
- Architecture design
- Data modeling techniques
- Principles like idempotency, change isolation, test driven development, automation, governance, consent, fairness

But process alone doesn't guarantee outcomes. A good review looks deeper: is the platform (and the team) set up for success?

Here’s what I look for:

🔹 Clear Value Creation
Does the team know what value they create? "We are faster or cheaper" isn't enough (a good data platform pays for itself). Real signs are documented business outcomes and financial impact.

🔹 Pragmatic Decision-Making
Is the team pragmatic or just following industry dogma? Strong teams show local, rational decision-making.

🔹 Long-Term Sustainability
Will the platform scale and survive the next wave of tech? Strong designs avoid shortcuts that lead to technical debt.

🔹 Team Dynamics and Leadership
Technical skill is not enough. Good teams communicate clearly, collaborate smoothly, and have engaged leadership that spends real time and mindshare.

🧠 Reviews are tiring and valuable. But even without a review, working through questions like these will help you to improve your own data platform.

👉 What criteria do you use when assessing a data platform or data team? Let's discuss in the comments!

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