Data Management

3 (More) Foundational AI Capabilities for IBM i

Rick Hurckes, director of services at mrc, shares how AI can fill gaps in IBM i environments that used to be addressed with workarounds and tribal knowledge

From Noise to Intelligence: How Taxonomy Is Essential to AI for Mainframe Operations

For the first article in their series, "Rise of the Agents," Clea Zolotow, Marci Formato and Alfredo Iglesias of Kyndryl discuss why flooding AI systems with unstructured or poorly classified information is insufficient

IBM i’s AI Advantage: The Ecosystem Stakes a Claim 

As a platform for AI, the OS has a leg up due to its comprehensive data sets, integrated architecture and unique user base, IBM i enthusiasts proclaim

Overcoming the Semantic Gap in Mainframe-to-AWS Schema Mapping

Connecting enterprise data to cloud platforms is the first step—understanding what it means is the next challenge, Tim Bond of Adeptia and Rohan Gupta of R Systems explain

From Transaction Logs to AI Insights: The Rise of Flow-Centric Data

Navdeep Sidhu, CEO of meshIQ, describes how an an end-to-end transaction-centric observability layer can fill in the "assurance gap" that exists with traditional monitoring tools

The DBA’s Role in a World That Thinks It Doesn’t Need DBAs

In a world of automation, AI and "self-managing" databases, the role of the DBA has become misunderstood, Craig Mullins writes

Agents in the Enterprise: How to Meet the AI Moment

Experts in AI and cloud infrastructure explain what enterprises and technology providers are doing to operationalize agentic workflows at scale

Manage z/OS Storage Without the Green Screen: A Unified Approach with UDM

From Technical Debt to Storage Mastery: Modernizing z/OS Management with UDM In the modern agile enterprise, Storage Resource Management (SRM) serves as the cornerstone of operational resilience. However, many organizations remain shackled to “monolithic legacy debt”, rigid architectures that have failed to evolve alongside the data center. When an infrastructure tool requires more effort to […]

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Automation Isn’t Accountability: Why the DBA Still Owns the Outcome on IBM Z

While there is real value in automation and much promise in AI, human expertise will still be required—because humans will still be accountable, Craig Mullins observes

Building Real-Time Data Pipelines to the Cloud Without Disruption

How enterprises can stream data from mainframe and Power systems to the cloud to support real-time analytics and AI applications