Marrying Structured + Unstructured Data: How vision data solves enterprise business needs

Track: AI

Main Auditorium

1:40 PM

Enterprises are generating more data than ever before but much of it is unstructured, particularly in the form of images and video. Traditional analytics and governance models excel at structured data like transactions, customer records, or sensor logs, but fail to capture the critical insights hidden in visual data streams. This session brings together two perspectives: enterprise data strategy and computer vision R&D. We will explore how computer vision turns raw pixels into meaningful features, enabling anomaly detection, quality control, and predictive maintenance across all industries. Once captured, these insights must be integrated into broader data ecosystems, when combined with structured data from an CRM, FPM or Data Lakehouse the value of your data increases. Marrying these two data types unlocks transformative outcomes: reducing operational downtime, improving customer targeting, increases productivity, and powering AI-ready enterprises. Attendees will walk away with an understanding of computer vision across an enterprise, combining images and structure data. We’ll highlight real-world examples on defect detection and institutional operations, while addressing the ethical and governance challenges of combining structured and unstructured data at scale. Whether you’re a technical builder, business strategist, or leader in AI adoption, this talk will equip you with practical strategies to connect vision-driven insights with enterprise value creation.