IDUG NA 2026

The Db2 family of products including Db2, Db2 Warehouse, and Db2 PureScale provide a number of important features for diagnosing and solving your SQL problems. Through a series of practical examples, this session will bring you up speed on the latest capabilities available for SQL diagnostics and show you how you can leverage them to solve query problems in your own environment. You will learn how to identify your most expensive SQL statements using the package cache table functions, and how to use Db2's "time spent" metrics to analyze where your problem queries are spending their time. You will also learn some new tips for monitoring sort memory metrics and query memory consumption in order to tune your analytic workloads. Finally you will learn how to use the runtime explain capabilities in conjunction with the activity event monitor to capture actual query plan cardinalities as well the per object metrics.

Db2 Z and the CIA is a powerful informational combination. To be clear, the CIA is the Compliance Information Analysis product available for free to many users of Db2 Z (if you have Broadcom products). Broadcom introduced the CIA as a subproduct of ACF2. It is now an independent product available to most users of their products. The CIA provides a series of Db2 tables that can contain all the information from your external-security-manager (ESM), whether it is ACF2, RACF, or TopSecret. Once your ESM is loaded into the CIA, it is relatively more accessible to the curious end-user! SQL SELECT can be used to easily build interesting and useful and focused reports about your security configuration. This presentation will go over the basics of mainframe security and the basics of the CIA and how to build and populate. Finally, interesting CIA tables and views (and sample SELECTs) will be highlighted to show why it is useful.

Even well‑written SQL can slow Db2 for z/OS when subtle mistakes slip through. In this hands‑on lab, attendees will work with preloaded queries that showcase common pitfalls—over‑indexing, missing or stale statistics, inefficient joins, unnecessary sorting, and predicate mismatches. You’ll identify the issues, apply targeted fixes, and validate improvements using metrics, access path analysis, and supporting tools.
Beyond immediate speedups, this lab reinforces a repeatable diagnostic approach that strengthens day‑to‑day tuning and sets the stage for AI‑assisted operations—where consistent, high‑quality data enables smarter automation and more reliable outcomes.

This hands-on lab will explore how Db2 integrates vector data with structured relational data to support AI-driven use cases. Through guided exercises, attendees will combine unstructured text-derived vectors with traditional data and apply similarity search across both. The lab shows queries that merge SQL filtering with vector similarity to enable semantic search, recommendations, and intelligent data retrieval.