8 | | FEBRUARY 2026IN MY OPINIONSHAPING THE FUTURE OF DATA SCIENCE THROUGH BUSINESS ALIGNMENTBy David Rodrigues, Data Governance & Data Management for Brazil, Philip Morris InternationalAligning Data Initiatives with Business GoalsThe most important part, often overlooked by data professionals, is starting with business priorities. Many CDOs and data leaders focus too much on tools and solutions, which can be risky. That approach often prevents data teams from delivering real value. Understanding the business end-to-end should always come first. Once that is clear, data and technology can be used as enablers to help the business reach its goals, not as ends in themselves. For me, that is the foundation of impactful data work.One of the biggest blockers today is data quality and governance. Many advanced tools, platforms and models are available, but without the right data, even the best solutions will fail. I have experienced this myself. Before I joined Philip Morris International, I deployed a recommendation model using the latest technology. Everything seemed solid, but when we put the model into production, the results made no sense. After some investigation, we discovered the issue was poor data quality and weak governance.This gap between ambition and execution is very common. Many companies invest in sophisticated tools without first ensuring their data is ready. That is why I believe the next few years will see a growing focus on data readiness, governance and quality. These elements are not just technical necessities. They are critical for strategy. The ability to connect business priorities with strong data foundations and the right technology will define success in the analytics space.Top Trends Shaping Data Science and AI I think the most obvious trend right now is AI agents. This is where the cutting edge is, and many companies are starting to explore their potential. Of course, privacy is a top concern. We take data privacy, security, and compliance very seriously. Strong safeguards and a responsible approach guide every step we take in the data space.AI agents are different from the bots and solutions we have seen before. They are more autonomous. They can sense what is happening and make decisions or take action without being explicitly programmed for each step. That level of autonomy is what makes them so powerful and potentially transformative.Without strong data governance and management foundations, companies will struggle to make real progress, even with the best tools. Many organizations will find their ambitions blocked by poor data readiness if they do not invest in quality and governance.David Rodrigues is Data Governance & Data Management for Brazil, at Philip Morris International, where he leads efforts to embed data-driven thinking into regional decision-making and business transformation. His career began in market research, working across sectors including finance, telecom and consumer goods, which gave him early exposure to how data informs diverse business models. Seeking to deepen his technical expertise, he pursued a master's degree focused on data science, statistics and machine learning.That shift led him into data science roles, including the pivotal position at Philip Morris International, where he applied advanced analytical methods to support commercial strategies. Over time, his scope expanded from modeling and insights to guiding broader data and analytics transformation efforts across markets. Today, Rodrigues bridges strategy and data execution, aligning analytics initiatives with core business priorities. In this feature, he reflects on how strategic alignment and trend awareness drive his approach to analytics, underscoring his leadership in scaling data initiatives across a complex regional landscape.David Rodrigues
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