IDUG NA 2026

IBM Bob makes a huge difference to understanding, modernising and administering systems developed with Db2 (both LUW and z/OS) as the underlying database. I will talk about my real-world experiences bringing IBM Bob into my workflow and the benefits it made in terms of efficiency and quality of the outcomes. I will also explain why I turned from an AI sceptic to enthusiast once I got hold of the right tools.
After struggling to get value out of other AI assistants when modernising and administering Db2 applications (both LUW and z/OS), I turned to IBM Bob when it became available. Having become an "AI assistant cynic" I quickly became a real enthusiast. IBM Bob understands the technology I am working with and provides real value, but in a way that leaves me always in control. This presentation describes my journey from initial experimentation to real world business value. I'll describe how IBM Bob facilitated system understanding, assisted with structural change and application modernisation.

Make sure you have all the tools to write functional SQL using all the features of recent versions of Db2. Stop writing SQL like it's the '90s.

There have been so many enhancements in Db2 SQL for developers in the last 3 or 4 versions that many developers have never really taken advantage of. This presentation picks my personal favorites that I believe all developers should get knowledgeable on and possibly applied to current and future applications. Developers should be informed of all of newer features in Db2 and this presentation is a great summary for this topic. When it comes to performance, often times the answer to better performance is rewriting queries different ways, and redesigning programs differently. Attendees will leave with a better understanding of some great SQL enhancements, application table designs, along with getting stronger in the SQL language. This is a great session for developers on Db2 LUW or Db2 z/OS. Developers 'Get Empowered'.

This session is about deep dive technical details of how Z data is integrated with other platforms and solutions. This is an architectural, use case and product level technical session. There will be latest news from the zSW Development and Product Management in the context of Data Management, focused on Db2 for z/OS.
The goal of this session is

What are data modernization Challenges – Past, Present, Future
IBM Z Data and AI Enterprise Architecture
Architectural alternatives to provide Db2 for z/OS data into other platforms for data modernization story
Core Products, Virtualization, Data Integration and AI Techniques
Replicate, Direct Access, Virtualization – Pros & Cons.
Technical and Business Use Cases with Capabilities
Roadmaps and Future direction of IBM

Security is often treated as an afterthought—apps launched without proper controls, cloud environments spun up outside organizational standards, third-party vendors granted excessive access to sensitive data. These missteps vary in form, but they all share a common denominator: data. And for attackers, data is the only thing that truly matters.
Regardless of how strong your perimeter defenses are, once an attacker gets inside, your ability to detect and respond quickly becomes critical. That’s where Guardium Database Activity Monitoring (DAM) comes in. DAM helps organizations understand what “normal” looks like—enabling real-time detection of anomalies, suspicious behavior, and potential breaches before serious damage is done.
In this session, we’ll explore how implementing IBM Guardium can reduce risk, improve incident response, and stop data leaks before they happen. Because when everything else can be bypassed, your best defense is knowing your data patterns.
Key scenarios we’ll examine include:- Privilege escalation and misuse- High-volume data extraction- Cross-site scripting (XSS) via database inputs- OS command injection through vulnerable queries- Abuse of privileged accounts- Unauthorized access to restricted or sensitive data- Password spraying and brute-force attempts- Anomalous behavior outside of baseline operations- Change reconciliation failures (e.g., Guard App event correlation)
For each use case, we’ll analyze:- What the attack looks like in terms of raw database activity- How DAM tools can be tuned to detect these patterns- Alerting and response workflows for containment and remediation

Twenty-one years ago, I joined IBM as a software developer. I knew nothing about AI. Today I am the AI Architect and Master Inventor of IBM Db2, leading vector search, in-database machine learning, and LLM integration.
How did the journey happen? Not the way I thought it would be. 

In this talk, I will share the blueprint I wish someone had given me earlier in my career: seven skills that took me from software engineer to AI architect. I will be honest about which ones moved me forward and which I learned too late. Some are technical. Most are not. They include learning AI from mentors, building communication as a craft, and learning to focus in an attention-fractured industry.

If you are an experienced software engineer wondering how to make the move into leading AI work, this talk is for you.

Db2 can be accessed from a wide variety of client platforms and languages. But information on the best way to achieve this access is often hard to find. This presentation will examine what Db2 clients are available and then look at the best way to configure connections from these clients. As well as the basic Db2 clients it will look at language and framework specific adapters as well.

The panel frames this discussion around the aspects most critical to enterprise database operations—the “Fantastic Four”: system capacity, performance optimization, cost management, and AI-driven analysis. Panelists will share real-world experiences and practical insights on applying AI to analyze database telemetry, anticipate workload changes, optimize resource utilization, and support data-driven decision-making at scale.By bringing together perspectives from multiple organizations, this session highlights how AI-enhanced database management is evolving from reactive monitoring to intelligent, predictive operations, helping enterprises improve reliability, efficiency, and business outcomes while managing growing data demands.