2026 - IMS/MachineLearning
2026 IMS/MachineLearning Track
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 6349
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 6120
Driving the future of IMS: 2026 IMS Modernization update
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
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Managing IMS is challenging on its own, but when regulations and external expectations stack up, the day‑to‑day upkeep can quickly become complex and exhausting. In this presentation, I’ll give you a glimpse into the realities of IMS housekeeping and what it takes to keep a 4 IMSplex running smoothly in a banking environment. We’ll look at the practices, routines, and safeguards that help us maintain stability, compliance, and performance in such a demanding setup.
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 5668
This introductory session is designed to demystify the Data Definition Language (DDL) within the context of IMS. Participants will gain valuable insights into the foundational structures of IMS DDL, understand how to define databases and segments, and learn the syntax that governs the creation and manipulation of IMS database hierarchies. By the end of this session, attendees will be equipped with the knowledge to confidently navigate the IMS-specific DDL, laying a solid groundwork for future endeavors in database management.
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 6330
With both internal and external cyberattacks on the rise, customers must deal with adherence to government regulations, fines for non-compliance, and most importantly negative publicity and customer impact if an attack does occur. While most customers have disaster recovery plans in place, recent events have revealed that DR is not enough in the event of a cyberattack. In this session, we’ll give a brief introduction to the IBM Z Cyber Vault solution, how it differs from DR, and how it can help customers reduce recovery time by providing an environment to help detect the attack sooner and verify recovery procedures before recovering to the production environment. Then we’ll dive a bit deeper into what this means specifically for an IMS environment.
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 5095
A lot of IMS systems were set up a long time ago, and have been kept that way for years under the mantra "if it ain't broken, don't mess with it". But what about when you do have to modernise things? This presentation will showcase a project of implementing IMS HP Tools, adopting IMS Catalog and IMS Connect, along with IMS managed ACBs, all in under a year, and future areas of consideration. Along with the lessons learned, a few useful tricks for populating IMS Catalog from old copybooks will be demonstrated.
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 6278
Securing IMS Connect Workloads
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 6130
Whilst the technical implementation of IMS Managed ACBs is not overly difficult, there are many other issues that need to be understood to make this a successful conversion.
In this session we will touch on why you need Managed ACBs, and cover many of the other issues that need to be considered.
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 5017
BoF.
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 4893
Securing IMS Connect Workloads.
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 4242
With the introduction of the IMS catalog, IMS has embraced a modern, metadata-driven approach to managing database and application definitions. The catalog stores metadata for DBDs, PSBs, and other critical resources in a structured format that can be queried using SQL. This opens new opportunities for developers, DBAs, and system programmers to access IMS metadata in a dynamic and flexible way—without relying on traditional static source libraries or manual navigation.
This session will focus on how to effectively retrieve and analyze IMS catalog data using SQL. Attendees will learn how to construct SQL queries to access DBD and PSB definitions, explore program-to-database relationships, and extract metadata to support auditing, DevOps pipelines, and system documentation. Real-world examples will demonstrate how SQL-based access to the IMS catalog streamlines system management, improves transparency, and enhances automation efforts in modern mainframe environments.
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- Parent Category: 2026 Helsinki
- Category: 2026 IMS/MachineLearning Track
- Hits: 6559
Do you need a modernized approach to performance monitoring and issue resolution for IMS systems? NRB will introduce how they leverage IMS Performance Analyzer, streaming and Grafana dashboards. The presentation will cover the architecture of the solution and the benefits gained from incorporating IMS data into a scalable analytics ecosystem.