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As enterprise AI scales, traditional data architectures are reaching their limit. Workloads are becoming more distributed, data movement is accelerating, and tech leaders face growing pressure to justify AI spend while delivering real business impact. Chief Technology Officer Sergio Gago breaks down key findings from Cloudera’s latest global survey of enterprise architects, data architects, and cloud leaders.

Qlik's MCP server just got three new lookup tools built for data engineering. They connect directly to your Qlik Cloud tenant, so coding agents can pull the real project values a pipeline needs instead of working from an empty template, find spaces and data connections by name, and browse the tables and views available on a connection, just by asking in natural language. That means easier declarative pipeline creation, with real tenant context built right into your prompt for faster, more accurate iteration.

Meet Winny, a GTM Intelligence agent built with AgentSpot and ThoughtSpot. See how teams can get faster answers to questions about conversion and pipeline velocity by simply asking questions in AgentSpot or Slack, with verified data pulled directly from ThoughtSpot. What is AgentSpot? AgentSpot is multiplayer AI for your business. Anyone can build, share, and collaborate with AI agents connected to your company’s data, context, and tools.

Most companies are investing in AI. Very few are seeing it reflected in their financial results. The gap comes down to three foundational decisions. In this clip from The Data & AI Chief, Raman Tallamraju from Vanguard breaks down what the companies seeing measurable AI benefits have in common.

Your next banking initiative shouldn't wait on another custom integration. Keep your core banking system and connect everything around it with Centerprise AI. Describe the pipeline you need, and it generates the connections, mappings, transformations, and data quality checks across APIs, databases, legacy systems, and more.