Interested in exploring IBM SQL Data Insights without the effort of installing it on your system or building models from scratch? This session introduces Industry Starter Kits designed to help Db2 for z/OS users quickly evaluate and experience the power of AI-driven insights using pre-built models, sample industry data, and ready-to-run AI queries. The session features real-world use cases across industries such as finance and insurance, demonstrating how SQL Data Insights can analyze Db2 table data to uncover hidden relationships, detect anomalies, identify unusual transactions, and generate meaningful business insights that may be difficult to find using traditional SQL techniques alone. Attendees will learn how to deploy and load pre-built AI models, execute AI-driven SQL queries, and understand and interpret the results returned by those queries using familiar Db2 workflows and interfaces. By walking through the industry use cases included in the starter kits, attendees will gain a clearer understanding of what SQL Data Insights is capable of and how AI-driven SQL analysis can be applied to their own Db2 environments. The session is intended to spark ideas for new use cases and help users envision how their existing Db2 data can be analyzed in entirely new ways. Whether you are new to SQL Data Insights or looking for an easier way to get started, this session provides a practical, hands-on approach to jump-starting your AI journey on Db2 for z/OS.
Jae Lee is a Senior Software Engineer at the IBM Silicon Valley Lab, specializing in the development of Db2 AI for z/OS, SQL Data Insights, and the Db2 RDS component.
Program Director, IBM Db2 for z/OS Development and Product Management, IBM
Catherine (Yan) Wu is the Program Director for Db2 for z/OS at IBM’s Silicon Valley Lab, leading Db2 for z/OS development and product management. A skilled engineering leader, her expertise spans database management, data governance, machine learning, and enterprise design thinking... Read More →
Monday October 26, 2026 3:20pm - 4:20pm EDT Magnificent 6