IDUG NA 2026

Not all indexes are created equal. We explore the architectural differences between Partitioned, Non-Partitioned (NPSI), and Data-Partitioned (DPSI) indexes and when to deploy each for performance. Crucially, we explore each type's optimal recovery strategy so you can stop guessing between Rebuild and Recover.

For decades, Db2 for z/OS DBAs have served as the platform’s human control plane, balancing availability, performance, recoverability, security, and change at enterprise scale. Today, automation, smarter tooling, and AI-driven recommendations are reshaping that role by reducing repetitive work and accelerating insight. But does that mean the DBA is disappearing?This session examines the past, present, and future of Db2 for z/OS administration to distinguish what can be automated from what still requires human expertise. It explores how autonomics, integrated monitoring, and operational AI are moving DBAs from manual execution toward policy, architecture, governance, and decision-making.Attendees will gain a practical view of where AI adds value, where it can mislead, and why deep Db2 expertise remains essential for interpreting signals in context, managing trade-offs, and responding when the unexpected happens.

This session will concentrate on customer experiences in Db2 13 and positioning of the next release of Db2. Where are most customers at in their Db2 13 experience, Function Levels, exploitations. What are the items customers are exploiting, utilizing and lessons learned in the endevor. Session will be a mixture of Db2 DBA and System Programmer viewpoints.

The future of Db2 for z/OS is Universal Table Spaces (UTS) with IBM signaling that the next version of Db2 will no longer support legacy structures.
At the same time, Db2 itself is evolving toward UTS, with catalog and directory objects already being prepared for conversion through future Db2 13 function levels—reinforcing that UTS is the long-term foundation of the platform.
Despite this, many environments continue to delay conversion. The result is growing data volumes, increased complexity, and higher risk when the transition eventually becomes unavoidable.
This session focuses on why UTS conversion is essential. Beyond the “why,” we will dive into the “how”—sharing real-world examples of conversion failures and lessons learned from the field.

After completing an assessment of IBM’s Bob, using Db2 for z/OS use cases, I was amazed and disappointed. This introductory session summarizes key items found during the assessment. I’ll demonstrate a Db2 for z/OS client and a System Profiles GUI created, both without writing a single line of code.

Db2 for z/OS continues to advance with new capabilities that simplify development, automation, and operations across the enterprise.
Join this session to explore the latest modernization updates including Db2 auto-discovery of configuration parameters, future exploitation around Configuration as Code, new APIs to support continuous integration and continuous deployment of database schema changes, and IBM Db2 Agents.

This presentation will demonstrate how ISPF panels and SQL are used to enhance IBM Db2 tools such as Omegamon PDB and CQM history tables. The Db2 V13 Utility history tables and In-house written Db2 health checks will also be presented. These solutions have been implemented at Navy Federal Credit Union with Db2 V12 and V13 mission critical applications.

With over 300 Db2 for z/OS subsystem parameters (zParms) constantly shifting, keeping your mainframe optimized can feel like chasing a moving target. Defaults change, deprecated parameters vanish, and critical new tuning options quietly debut - leaving many organizations running on legacy configurations that secretly drain performance and inflate costs. When was the last time you truly audited yours? Join this session to demystify the modern zParm landscape, uncover hidden configuration traps, and walk away with a battle-tested blueprint of industry best practices to supercharge your Db2 environment.

Distributed client applications (from a server) are the most important and common of new workload using Db2 Z.
There are many concepts and terms thrown around which we often too often gloss over without a complete understanding.
This presentation will re-explain basic terms from my user perspective plus share some experiences learned (the hard way?) over recent years.
This presentation covers THREADS and DBATS and CONNECTION. What they mean and how they work and what our Db2 can tell us about their usage and importance.

In today’s busy environment, there is a lot of pressure to automate as much as possible. To that end, and lacking AI tools to do my job, I have come up with a few shortcuts that allow me to automate some normally onerous tasks. In this presentation, I will describe and document some tasks I have automated in my shop. Hopefully some of this will prove useful.

Organizations that have optimized institutional data through governance, stewardship, and quality management are AI‑ready by design. Leveraging that institutional data both internally and externally for competitive advantage opens possibilities at scale never before imagined. This session will discuss:
Tool adoption without data maturity creates risk: Weak data foundations lead to unreliable results, reduced transparency, and diminished business value.AI builds on existing data foundations: Incremental enhancements—such as data scraping, enrichment, and feature refinement—are most effective when layered on curated data stores.Efficient access to data still matters: AI tools need immediate access to data.Data curation presents as a DBA responsibility: DBAs control data curation through standard operating procedures and best practices. Decision engines still matter: AI outputs are only as effective as the decision logic, controls, and context in which they operate.AI is an evolution of data expertise, not a replacement: The role of data professionals becomes more critical, installing guardrails in automation and scalable intelligence.This session reframes AI success as the amplification of long‑standing data discipline. Attendees will gain practical insight into what they are doing today, for better or worse, that is curating data and what approaches they can apply to improve AI positioning. Best practices in database management are not a preparatory step for AI, but translate directly into sustainable AI advantage.