Treat Your Data Like People: Lessons for Better Data Quality

Hi deer readers!

Today we’re re-posting a fantastic interview created by our friends at Hyperight – the masterminds behind the top data and analytics events in the Nordics. They’re building an incredible community for data and analytics practitioners, and we absolutely love them!

We’re thrilled to be joining them with the Deerdata team – both as speakers and participants – at the upcoming Data Innovation Summit in Kista, May 7–8.🎟️ Get your tickets here !

Below you’ll find an interview with our CEO Josefine and one of our amazing customers, Gunilla Thorén, Head of BI & Analytics at Volkswagen Group Sweden. Together, they’re exploring the wild idea that data should be treated like people.
…Does that mean we’re supposed to feed it cake too? 🍰 Read on to find out!

What if organizations treated their data with the same care they reserve for their people? That’s the idea behind the upcoming talk by Josefine Boqvist and Gunilla Thorén at the Data Innovation Summit 2025! With decades of experience in data, analytics, and AI, Josefine and Gunilla are reimagining how we approach data governance, quality, and culture, starting with a simple mindset shift.

In this interview, they share their journeys, what sparked the idea of “treating data like people,” and why organizations still struggle with basic data quality. They discuss the practical steps needed to create data ecosystems that are not only more automated, but also more human-aware. Whether you’re beginning your data transformation or looking to scale AI responsibly, their insights offer an approach to building trust in data.

Keep reading to explore how rethinking data through a human lens can unlock smarter strategies, stronger collaboration, and a more data-literate future.

Gunilla and Josefine, can you share a bit about yourselves, what is your professional background and current working focus?

Gunilla Thorén & Josefine Boqvist

Hyperight: Treating data like people is the topic of your presentation at the Data Innovation Summit 2025. Can you explain how this concept emerged, and why it is so important for organizations today?

Gunilla Thorén: The concept of treating data like people is actually the brainchild of Josefine, so I can’t take credit for it. We’ve noticed that many people, including senior executives, struggle to grasp the importance of data quality and data governance.

To make this easier to understand, we’ve often used an analogy that resonates with them. In meetings, we’ve called participants by different names, which naturally leads to confusion and chaos. This is exactly what happens with data. Just as each person has a name, data needs to have a consistent name that everyone agrees on.

Josefine Boqvist: Yes, exactly – for me, this concept really emerged from a need to tell better stories around data. It’s often overlooked or misunderstood, and yet we’re expecting data – and increasingly, agentic AI – to take on more and more responsibility in our organizations.

It’s only fair that we treat data with the same maturity and structure that we apply to people. Think about it: we have roles, responsibilities, onboarding processes, and accountability frameworks for employees – but we often lack all of that for our data. This analogy helps make that gap visible and sparks important conversations about the way we manage and trust our data.

Hyperight: In your experience, what is one common misconception organizations have about data quality, and how can they overcome it?

Josefine & Gunilla: One common misconception organizations have about data quality is that it is solely the responsibility of the IT department. And, with a one time effort, all quality issues can be solved.

Hyperight: What are some of the most surprising parallels you’ve drawn between managing data and managing people? Can you give us an example?

Josefine & Gunilla: What has surprised us the most is the number of parallels that can be drawn between managing people and managing data. But no spoilers now! You’ll have to come to our presentation at the Data Innovation Summit to hear more about these fascinating parallels.

Hyperight: For organizations just starting to think about improving their data quality, where should they begin? What are the first steps to take?

Josefine & Gunilla: Take it step by step. Instead of heavily investing in new tools and a 50 page strategy, start working with the data quality issues that give you the most trouble.

Hyperight: Josefine, as the CEO and founder of Deerdata, you’ve worked closely with Nordic businesses to help them leverage data. What have you seen as a barrier to data adoption, and how do you help clients overcome it?

Josefine Boqvist: Many organizations invest in tools and platforms, but they haven’t built the mindset or the habits needed to actually use data in day-to-day decisions.

At Deerdata, we focus on making data practical and relatable. That means starting with real business problems, simplifying the language, and helping teams feel ownership of the data they use. We also put a lot of emphasis on storytelling and activating data through clear, actionable insights – not just dashboards that look good. It’s about bridging the gap between tech and business, and making data part of how people work, not something extra on the side.

Hyperight: Josefine, your leadership approach emphasizes collaboration and turning complexity into actionable insights. How do you bring that into the world of data and AI, when businesses may not have a clear data strategy yet?

Josefine Boqvist: I believe data and AI have the potential to transform not just how businesses operate, but how they think. But when there’s no clear data strategy in place, the key is to start by creating clarity – not by adding complexity.

My approach is about turning ambition into action. I bring people together across functions and help them see data not as a technical project, but as a strategic asset that can unlock entirely new ways of working.

Hyperight: Josefine, you’ve held senior roles, such as Head of Analytics IT at Telia. What were some of the data-related challenges you faced there, and how did you approach them?

Josefine Boqvist: Different kinds of data quality issues were often at the core – from siloed data and unclear ownership to a lack of understanding around how data should actually be used. There was also a strong focus on technology, while the real business use cases were sometimes not understood.

One of the biggest wins was breaking down silos – not just in the data itself, but also between business and tech. By building shared ownership and aligning around real outcomes, we were able to turn data from a technical challenge into a strategic asset.

Hyperight: Gunilla, you are leading the data and analytics transformation project at Volkswagen Group. How do you balance the need for modern technology with the organization’s existing data infrastructure and legacy systems?

Gunilla Thorén: Balancing modern technology with legacy systems is always one of the biggest challenges in any data transformation. At VGS, we prioritize what matters most first and take a strongly business-driven approach. We try to combine the foundational work – platform modernization– with the new parts, such as exploring generative and agentic AI at the same time.

It’s a balanced approach. While we’re modernizing step by step, we’re also investing in education and capability-building across the organization to ensure everyone can be part of the journey.

Hyperight: Gunilla, with expertise in data modeling and BI architecture, what do you consider the most crucial factors for ensuring that a data model is both scalable and effective for decision-making at all levels of the business?

Gunilla Thorén: Keep data granular; you can always aggregate it for management reports. Your data models should mimic the business processes and work with reusable dimensions. Using reusable dimensions simplifies not only the creation of reports but also the development within the data platform and the requirements gathering process. As a bonus, it makes it easier for users to understand and interact with the data.

Hyperight: Gunilla, data literacy is a key focus for you. How do you approach improving data literacy within an organization, and what impact has that had on Volkswagen’s ability to leverage data effectively?

Gunilla Thorén: I don’t have any quick fixes – I believe we are doing what many others are as well.

1. Education and Training: We focus on providing comprehensive training programs to improve data literacy across the organization.
2. Promote a Culture of Data-Driven Decision-Making: This involves not only providing ready-made dashboards but also implementing a self-service strategy where everyone has the opportunity to contribute to our dashboards in a controlled manner.
3. Implement Data Governance: Ensuring data quality and consistency through clear governance policies. Creating clear definitions is of no value if they are not used and known. Therefore, we have developed a chatbot to assist with this.

Hyperight: Gunilla, in your opinion, what are the most common pitfalls organizations face when trying to build an automated data ecosystem, and how can they avoid them?

Gunilla Thorén: It’s a hard on! I can think of many different mistakes. But I will overlook the importance of data quality. Data quality issues were the reason our first large use case on our new data platform got delayed.

Hyperight: Looking ahead, what do you think the future holds for the relationship between data and people?

Josefine & Gunilla: We believe the relationship between data and people is only going to deepen. As AI becomes more integrated into our work and lives, data will move from being something we analyze about people to something that actively supports and collaborates with people.

But for that to work, trust is key. We need to design systems where data is accurate, responsibly handled, and clearly understood. And that starts with treating data with the same care and intention we give to people.

If you’re ready to rethink your data strategy from the ground up, don’t miss Josefine and Gunilla’s session at the Data Innovation Summit 2025. They’ll dive into the concept of “treating data like people,” sharing real-world lessons from their work at Deerdata and Volkswagen Group Sverige. You’ll hear how organizations can build trust in data, avoid common pitfalls in quality and governance, and make data a truly collaborative asset.

For leaders looking to boost data maturity, spark cultural change, or unlock the full potential of AI, this talk offers both inspiration and actionable steps. Don’t miss the opportunity to learn how a more human-centered approach to data can drive better decisions and better business outcomes!