Robin Sutara, Field Chief Data Strategy Officer at Databricks, speaks with Robert Lutton, VP, Sales and Marketing, Sandhill Consultants, in a video interview about siloed data systems, commitment to proactive solutions, transforming data engineering with Lake Flow, democratization, and embracing change.

Sutara underscores the dangers of siloed data systems within organizations. She says, “The more siloed your data, the more security complexity you’re introducing to your organization.”

She notes that by minimizing silos, whether across different platforms or infrastructures, organizations can manage risk more effectively and streamline oversight.

Proactive AI risk management framework

Moving beyond reactive security practices, Sutara highlights Databricks’ commitment to proactive solutions. A key initiative in this direction is the Databricks AI Security Framework, now in its second version.

The second version has 66 factors that serve as a comprehensive guide for organizations to evaluate their AI security posture, helping them maintain innovation while minimizing risk. “These in-depth controls actually allow them to simplify their AI risk management and get alignment across the organization on the things that matter.”

Real-world impact: A case study from the financial sector

Next, Sutara shares how one of the top 20 U.S. banks has adopted the framework to develop internal guidelines for AI security and modeling.

“One of the top 20 US banks is actually using this framework to roll out internal guidelines around AI security and AI modeling so that everyone is following the same frameworks and the same standards and understands the risks that are relevant for the bank.”

The results have been significant. By aligning on security standards, the bank reduced its vendor due diligence time by 66%, she adds.

Sutara emphasizes that while every organization has unique needs, especially those in highly regulated industries, the framework offers a solid foundation. “We want to make sure that everybody has an initial framework that they can start with.”

Transforming data engineering with LakeFlow

Moving forward, Sutara highlights the remarkable pace of innovation at Databricks, especially in the realm of data engineering. She points to a key area of focus announced last year: disrupting traditional data engineering practices.

Many organizations struggle with managing the end-to-end process of data ingestion, pipeline development, and orchestration. To address this, Databricks introduced LakeFlow, a comprehensive solution designed to streamline all stages of data engineering — from ingestion to transformation and orchestration.

The first component of LakeFlow, LakeFlow Connect, specifically tackles the challenge of data ingestion. Sutara explains, “LakeFlow Connect is the first of the three components that helps solve that ingestion problem. How do you pull from every data source?”

She refers to existing integrations with systems like Salesforce and Workday as examples, enabling seamless data ingestion. Once ingested, data can then be processed using DLT (Delta Live Tables) for transformation and orchestrated using Databricks Workflows.

According to Sutara, many organizations are already leveraging these capabilities as a critical first step in modernizing their data infrastructure.

Empowering the future of work: Democratization, AI, and embracing change

With a role that puts her in close contact with customers around the world, she sees firsthand the opportunities and challenges facing modern enterprises. For Sutara, the biggest opportunity ahead lies in deepening the democratization of data and technology access. She sees the convergence of natural language, AI, and tools like BI and Genie as foundational steps in this movement.

Furthermore, Sutara anticipates a growing role for agent-based systems, which will move beyond simple use cases and begin transforming how organizations design and deliver their products and services.

Reflecting on how conversations around data have evolved, Sutara recalls a time when data monetization was the dominant narrative. Now, the focus has shifted to organizational disruption — unlocking the collective intelligence of the workforce.

“I remember 10 years ago I felt like all we were talking about was monetization of data. But today, organizations are thinking about their disruption and what they could uncover if they could unlock the power of the intellect that exists across their organization.”

This shift demands that organizations free their people from routine, low-value tasks — many of which no longer require human intervention. To drive transformation, Sutara stresses the importance of simplifying user experiences, especially through interfaces modeled on tools people already use, like ChatGPT.

Preparing for a future of continuous change

Sutara sees the next five years as critical for preparing people, not just technologically but mentally, for a world where change is constant.

“How do we get people comfortable with the fact that change is a daily activity that’s going to happen in technology and data? And how do we get them to embrace that and see it as an opportunity as opposed to a risk for them?”

As organizations become more comfortable with automation and agent technologies, she believes the door opens to solving more complex and meaningful problems, those worthy of human creativity and focus.

CDO Magazine appreciates Robin Sutara for sharing her insights with our global community.