How Dailymotion Built a Modern Data Culture (And Made It Stick)

Inside Our Data Breakfast: How Dailymotion Transformed Its Data Strategy

This Tuesday morning, with coffee in hand and the smell of fresh croissants in the air, a group of data leaders gathered for our latest Data Breakfast. The guest of honor? Marie-Laure Lecompt, director of data product at Dailymotion. And let me tell you, her talk was anything but a rerun.

From “Data on Demand” to Full-Fledged Data Products

“We used to deliver data on request. Now we design analytics products.” That’s how Marie-Laure kicked things off, and from the very first slide, you could feel the shift. Dailymotion has undergone a full-blown data transformation, moving away from reactive analytics toward a modern, product-oriented data platform.

Instead of analysts scrambling for ad hoc insights, they’ve built a robust, scalable foundation with governance, observability, and self-service capabilities for everyone from engineers to business users. Even a few AI agents are starting to get involved.

“I used to spend hours hunting down the right dataset,” Marie-Laure joked. “Now people complain if insights aren’t embedded directly into their tools. I take that as a win.”

✨ Quick plug: if you're new to data observability, check out our guide on to assess your need for data observability. Spoiler: it’s about more than just firefighting.

Real-World Use Cases (No Buzzwords, Promise)

This wasn’t one of those vague "data transformation" talks. We got the good stuff. Concrete examples that showed how a thoughtful data strategy actually drives value.

One example focused on forecasting ad inventory availability. The feature is now embedded into internal tools and helps sales teams deliver campaigns with better precision and less manual work. The result? More confidence in forecasting and fewer last-minute fire drills.

Another centered on delivery monitoring. By rebuilding the pipeline and embedding analytics into internal platforms, Dailymotion reduced storage costs, improved performance, and gave teams a single, trusted source for delivery data. Goodbye data sprawl, hello operational efficiency.

Each of these projects followed a clear, phased roadmap. And they were built through collaboration across data, engineering, and business teams. No silos. No ivory tower.

Culture Eats Data for Breakfast

One thing that stood out? How seriously Dailymotion takes data culture. They’ve rolled out a full-on enablement program with starter kits, trainings, regular rituals, and even office hours with data experts.

“We knew tools alone wouldn’t be enough,” said Marie-Laure. “If people don’t trust the data or know how to use it, they won’t use it at all.”

And that’s exactly why observability and discoverability are baked into the ecosystem. The goal isn’t just adoption. It’s confident, autonomous decision-making. Across the board.

Want to dig deeper? Check out “Top 7 Reasons Why Data Observability is Critical for AI-Powered Organizations in 2025”.

What’s Next? AI-Ready Data

The final part of the presentation looked to the future. With a strong foundation in place, Dailymotion is turning its attention to making data usable by and for AI. That means high-quality inputs, clear documentation, observability at every level, and streamlined access.

This resonated with many of us at Sifflet. We’re seeing the same shift across our customer base. Everyone wants AI, but not everyone is ready for it. Reliable, observable, well-documented data is the prerequisite. No shortcuts.

TL;DR?

Dailymotion’s journey is a blueprint for what a modern data organization can look like. Practical, collaborative, and genuinely inspiring. Huge thanks to Marie-Laure for sharing her story with such clarity and humor. And for managing to make a room full of data people laugh before 10 a.m. That might be the real miracle.