Building a Strong Data Foundation: Insights from Citigroup’s Analytics Leader

At Starburst, we believe that understanding how industry leaders like Citigroup approach data strategy can offer valuable insights for businesses aiming to maximize the value of their data. In a recent discussion between our CEO, Justin Borgman, and Murli Buluswar, Head of U.S. Consumer Analytics at Citigroup, several crucial learnings were highlighted that underscore the importance of a strong data foundation and strategic mindset.

Embrace a proactive data culture

One of the standout points from Murli was the necessity for data professionals to shift from a reactionary to a proactive mindset. Instead of merely responding to queries, data teams should shape the questions and drive the narrative. Cultivating a culture of curiosity is essential. This involves encouraging team members to not only execute tasks but to understand the broader business context and the impact of their work. As Murli emphasized, creating a fertile ground for curiosity can significantly enhance the value derived from data.

Prioritize data infrastructure and accountability

Murli pointed out a common pitfall where companies overly focus on infrastructure without understanding its implications. It’s crucial to balance infrastructure development with accountability, ensuring that the infrastructure directly drives business outcomes. A robust data foundation is essential, but it must be coupled with a clear vision of how it supports the organization’s strategic goals.

From proofs of concept to strategic blueprints

Another critical takeaway was the tendency to engage in proofs of concept (POCs) without a comprehensive blueprint. Murli advocated for a strategic approach where POCs are driven by well-defined objectives and success metrics. This approach ensures that POCs are not just experimental but are aligned with the long-term vision and goals of the organization. As a vendor, we at Starburst resonate with this perspective, as it aligns with our focus on delivering proof of value rather than mere POCs.

The intersection of AI and decision making

In discussing AI, Murli stressed the importance of viewing AI not just as a tool but as an enabler for reimagining business processes. AI should serve broader strategic objectives, helping to automate mechanized tasks and elevate human intelligence for more complex, creative decision-making. This holistic view ensures that AI implementation drives tangible business value and aligns with core business processes.

Metrics and success measurement

Effective measurement of success was another key area of focus. Murli highlighted the importance of having clear, agreed-upon metrics that span financial outcomes, user engagement, and error reduction. These metrics provide a comprehensive view of the impact of data initiatives, ensuring that all stakeholders have a common understanding of success and its implications for the business

Future of human and machine collaboration

Looking ahead, the conversation touched on the evolving roles of humans and machines in the data landscape. Murli noted that while machines excel at processing and synthesizing data, the human role will increasingly focus on creativity, interdisciplinary thinking, and asking future-shaping questions. This shift underscores the need for continuous learning and adaptation among data professionals to stay relevant and drive business innovation.

Conclusion

Our discussion with Citigroup’s Murli Buluswar underscores the critical importance of a robust data foundation, a proactive and curious data culture, and strategic alignment of AI and analytics initiatives. These insights are invaluable for any organization looking to harness the full potential of their data assets.

At Starburst, we are committed to supporting our customers in building and optimizing their data strategies. By leveraging our open lakehouse platform, businesses can achieve the scale and cost-efficiency of a data lake combined with the performance of a data warehouse, enabling them to unlock new levels of data-driven intelligence and decision-making.

Check out the full session: