Why Better Data Starts with Better Questions: Insights from the World Data Summit

In a world where "more" is often mistaken for "better", the World Data Summit served as a powerful reminder that when it comes to data, quality always trumps quantity.

Tiago Afonso, Data Engineer at Mercedes-Benz.io, left the summit not only inspired, but with his perspective on data’s role in modern decision-making fundamentally shifted. In this article, we dive into Tiago’s reflections and what they reveal about the future of data, trust, and how companies like ours can stay ahead by asking better questions, building stronger frameworks, and rethinking what “data-driven” really means.

Challenging Assumptions: Why “More Data” Doesn’t Always Mean “Better Insight”

The talk that left the biggest impression on Tiago didn’t involve flashy dashboards or new tools—it was a deep dive into the messy reality of web analytics.

What made it so impactful? The topic hit close to home. The session explored how large datasets—especially those gathered from web activity—are often partial, fragmented, or distorted. Whether due to privacy blockers, data bottlenecks, or technical constraints, what we collect is rarely the full picture.

And yet, this is the very data we often use to drive decisions.

“It challenged the assumption that more data equates to better insights,” Tiago explains. “What really matters is the quality of the data, and how you account for its limitations.”

The session presented different ways of approaching these challenges, from new tracking methods to client-side and server-side trade-offs, all aimed at improving the integrity and usefulness of the data. For Tiago, it was a call to rethink not just how we collect information, but how we validate it, trust it, and act on it. 

Building Smarter Infrastructure: Lessons from an Open Source Movement

Beyond individual tools or tactics, the Summit also highlighted a bigger trend: a growing commitment across the industry to transparency, collaboration, and Open Source practices.

This resonated deeply with Tiago, who sees many parallels with the culture at Mercedes-Benz.io.

“A lot of companies are moving toward Open Source software and data-driven infrastructures,” he shares. “The ones that do this well are the ones that prioritize data at every stage—capturing it, processing it, using it—while still respecting compliance and privacy.”

But infrastructure alone isn’t the whole story. Tiago points out the importance of cross-functional collaboration. From engineers to analysts, designers to stakeholders, the entire pipeline needs to work in sync. Only then can we move from data as an input to data as a living, breathing resource.

Governance, Trust, and the Invisible Framework Behind Every Dashboard

When we talk about data in tech, we often gravitate toward the exciting stuff—new platforms, visualizations, machine learning breakthroughs. But Tiago’s takeaways from the Summit place just as much emphasis on something less flashy, but just as vital: governance.

“It’s not just about technology,” he says. “It’s about having a strong framework that includes risk analysis, clear responsibilities, user needs, and stakeholder alignment.”

In other words, it’s about trust. And trust doesn’t happen by accident—it is built intentionally.

The more we strengthen our internal governance models, the easier it becomes to access, share, and reuse data. And when people trust the data they’re working with, their confidence in making informed decisions grows as well.

This, in turn, leads to a rise in data literacy across teams—a ripple effect that transforms not just outcomes, but culture.

The Role of AI: Assistant or Architect?

Of course, no modern data conversation is complete without talking about AI. At the Summit, its role wasn’t positioned as a buzzword, but as a legitimate contributor across all stages of the data pipeline.

From cleaning and categorizing to analysis and prediction, AI has the potential to enhance how we handle data. But as Tiago notes, it cannot replace critical thinking or human oversight.

“AI can help us a lot, but trust still comes from transparency and sound processes,” he reflects.

It is not about automating everything. It is about using AI to amplify what matters most — accuracy, speed, and accessibility — while never losing sight of responsibility.

After World Data Summit, the Future of Data Is…

We asked Tiago to finish this sentence, and his answer was short, bold, and full of possibility:

Smarter, more accountable, and with unlimited potential.

That’s not just a prediction. It is a challenge. One that we can rise to by thinking critically, collaborating openly, and always choosing purpose over assumption.

From Insight to Action: Rethinking the Way We Work with Data

Tiago’s reflections from the World Data Summit are more than just food for thought. They serve as a call to action. A practical reminder that doing data well is less about the tools we choose and more about the choices we make. At Mercedes-Benz.io, we have the opportunity to turn these insights into practice.

That starts by shifting the spotlight from more to better. Data quality must be at the centre of our approach. Before we act on any insight, we need to ask the tough questions: Is this complete? Is it accurate? What might be missing?

Just as important is the need to reinforce governance. Robust frameworks that clearly define roles, manage risk, and reflect both user and stakeholder needs will always outperform ad-hoc decision-making. Governance isn’t about bureaucracy, it’s about building confidence in our systems. None of this works in isolation. Cross-functional collaboration, the kind that invites engineers, analysts, designers, and strategists into the same room, strengthens our outcomes. The more perspectives we bring to the table, the more resilient our data practice becomes.

There’s also room (and need) to lean into transparency. Whether through Open Source tools, open frameworks, or just open conversations, the companies that share knowledge openly are the ones that continue to grow.

And finally, we must remember that AI, no matter how advanced, is not a replacement for judgment. It’s a support system. If we build with intention and stay aligned with our values, AI can help us scale our impact without compromising our standards. This shift in mindset is what makes all the difference.

The World Data Summit made it clear that the future of data won’t be shaped by those who collect the most, but by those who use it with clarity, accountability, and purpose. That’s the challenge. And the opportunity.