A Structured Framework for Building Successful Data Solutions
•
Frederic Vanderveken & Kris Peeters
In this episode we talk with Frederic Vanderveken about a practical framework to make sure you’re building the right data solutions.
Most big data initiatives fail. In this episode of The Data Playbook, Kris talks with Frederic Vanderveken about a practical framework to make sure you’re building the right data solutions before a single line of code is written.
Instead of starting from tech (platforms, LLMs, tools), Frederik shows how to:
Align with business strategy first
Find a small, motivated customer team (e.g. marketing, operations)
Run problem discovery interviews that reveal real pains, not just annoyances
Map the current journey and treat existing workarounds as your competition
Identify value gaps along dimensions like simplicity, integration and automation
Prioritise solutions with five lenses: customer, growth, money, pragmatic, differentiator
Use the scientific method and experiments (MVPs, fake backends, low-code) to validate assumptions
Build a quantifiable business case and define clear success metrics upfront
If you’re a Head of Data, CDO or data product owner tired of “cool” projects that don’t deliver value, this episode gives you a concrete playbook to select and validate your next big data initiative.
🎧 Listen to more episodes of The Data Playbook for real-world stories on data platforms, GenAI, data products and cloud independence from Europe’s leading data practitioners and leaders.
🌐 More at https://www.dataminded.com/resources and subscribe to our channel: https://www.youtube.com/channel/UCxi05zIoV9bm69OAUmRoUDQ?sub_confirmation=1
Latest
Why AI Agents Need Knowledge Graphs, Not Just Data
Very few companies manage 10,000 of anything. Eric Broda on scaling AI agents like data mesh scaled data products.
How Tomorrowland Keeps Data Simple While Scaling Globally
Why simple data platforms outperform complex stacks, and how AI changes delivery without changing the fundamentals.



