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Cloudera Agent Studio & Iceberg MCP to Monitor Table Health

Jul 15, 2026 By Cloudera, Inc. In Cloudera

In this video, Cloudera’s Dipankar demonstrates how to build an AI agent in Cloudera Agent Studio powered by an open-source Apache Iceberg MCP Server. As a real-world use case, the agent monitors Apache Iceberg table health by analyzing metadata for issues such as small files, partition skew, snapshot history, and other operational signals. Subscribe to stay ahead of the curve with the latest in data strategy, open architectures, and enterprise AI innovations.

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The Gap Between AI-Capable and AI-Ready

Jul 14, 2026 By Tena Coppedge In Hitachi Vantara

Most enterprises are spending on AI faster than they’re becoming ready to run it. Over the next two years, IT leaders plan to grow their AI investment by 70%, according to our 2025 State of Data Infrastructure Global Report. The capability keeps arriving. The readiness to operate it does not keep pace.

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Agentic AI Test Execution Inside Jira with Xray and Lynqa

Jul 14, 2026 By Mariana Santos In Xray

AI is becoming part of every stage of the testing lifecycle. Teams are using it to analyze requirements, design test cases, generate automation scripts, and accelerate execution activities that previously required significant manual effort. Within Xray, AI already helps transform Jira requirements into actionable test cases with AI Test Case Generation.

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Xray

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How Agentic AI and Cloudera are Transforming Crisis Response

Jul 14, 2026 By Cloudera, Inc. In Cloudera

Can AI actually save lives? In this video, see how Cloudera and Mercy Corps have partnered to put people—not just technology—at the heart of humanitarian aid. Through a two-and-a-half-year collaboration, we’ve worked side-by-side with analysts to map real-world workflows and co-create AI solutions that solve their most pressing daily challenges.

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AI requires unstructured data to unlock its full potential

Jul 14, 2026 By Jamie Cole In Fivetran

Fivetran helps you turn unstructured data into rich context in several ways.

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Fivetran

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AI is Exposing Observability's Dirty Secret

Jul 14, 2026 By Speedscale In Speedscale

The 3 pillars of observability are breaking. For years, dev teams relied on Logs, Metrics, and Traces to know when something went wrong. But now? AI agents are writing, deploying, and changing code in real-time. When an AI hallucination pushes a bug to production, standard monitoring sees nothing wrong.To survive the AI era, we need a 4th Pillar of Observability. Watch to find out what it is and why the old way of monitoring just became obsolete.

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The Skill AI Can't Generate: Why Discernment Is the New Data Literacy

Jul 14, 2026 By James Fisher In Qlik

For more than a decade, I have argued that the most valuable skill in a data-driven organisation is not access to information. It is the judgment to know when that information is wrong. AI has made that skill more important, not less. When I wrote about AI literacy in 2023, the pushback I heard most often was that the technology was not yet good enough for the question to matter. Now it is. AI can generate answers, summaries, recommendations, code, analysis, and increasingly, actions.

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Xray and Lynqa: Agentic AI Test Execution in Jira

Jul 14, 2026 By Mariana Santos In Xray

AI is becoming part of every stage of the testing lifecycle. Teams are using it to analyze requirements, design test cases, generate automation scripts, and accelerate execution activities that previously required significant manual effort. Within Xray, AI already helps transform Jira requirements into actionable test cases with AI Test Case Generation.

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Xray

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Will AI Replace Manual Testers? Katalon's Data Says the Story Is More Complicated

Jul 13, 2026 By Monty Bagati In Katalon

If you only follow the loudest headlines, it is easy to believe AI is about to wipe out manual testing. Katalon's State of Software Quality Report 2025 tells a more useful story, and it comes from inside the industry: over 1,500 QA professionals, from individual contributors to senior executives, across North America, Europe, and Asia-Pacific.

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Enterprise test management: Should you build or buy in the age of AI?

Jul 13, 2026 By Klaudia Makiej In SmartBear

AI has opened the door for teams to build tools they previously had to buy. With the right prompts and internal workflows, teams can generate test cases, summarize results, analyze defects, and automate parts of the testing process faster than ever. For enterprise QA and engineering leaders, that raises a practical question: “should we build our own test management layer, or adopt an AI-powered test management platform?” It’s a fair conversation to have.

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