PANEL DISCUSSION: DATA ENGINEERING SYSTEMS TO DRIVE ENTERPRISE DIGITAL TRANSFORMATION OPTIMIZATION & ENHANCED BUSINESS OUTCOMES

Behind every successful AI and automation initiative lies a powerful - yet often invisible - data engineering foundation. For global enterprises, building this foundation means ensuring that data is accurate, accessible, secure, and architected for scalability across complex ecosystems.

Today’s data engineering leaders are enabling the enterprise of the future: one where data pipelines fuel real-time insights, AI models operate on trusted data, and governance is embedded into every layer of the data lifecycle. They’re tackling the hard questions - how to unify legacy and cloud environments, manage data quality at scale, optimize cost and performance, and ensure that the data powering AI is reliable and compliant.

Topics of discussion will include, yet will not be limited to:

• Building scalable data pipelines that enable AI, analytics, and automation across the enterprise
• Ensuring data quality, integrity, and governance in hybrid and multi-cloud environments
• Balancing agility, performance, and cost efficiency in modern data platforms
• Architecting trusted data foundations for enterprise-grade AI and decision intelligence

James Gowen, Ph.D., Global Head of Data Engineering Controls - Data Quality Platforms, CITI

Karthik Josyula, Head of Data & AI Platforms - Data & Analytics, KOHLER

Sumit Abhichandani, Global Director of Quality Assurance, VISA

Moderator/Speaker: Gaurav Sharma, Associate Director, Quality Engineering, LTIMINDTREE