Why AI Models Fail Without Trust | The Ontology Secret

Data trust is broken. In the "good old days," one expert vetted one dashboard. Today? You have massive scale and AI models that need accurate data to survive. Jessica Talisman joins Cindi Howson on The Data & AI Chief to reveal why the ontology pipeline is the secret sauce for trustworthy AI. Learn how structural clarity turns data chaos into your biggest competitive advantage. Catch the full discussion on your preferred podcast player!

What's New in ThoughtSpot's Latest 26.4 Release

Check out what’s new in ThoughtSpot’s latest release. dbt MetricFlow Integration: Seamlessly import semantic definitions from dbt for a single source of truth across your stack. AI Theme Builder: Stop mapping CSS. Describe your brand guidelines and watch a polished UI appear instantly. Enhanced Mobile Experience: Bring decision-making to your pocket with expert-level reasoning via Spotter 3 and mobile-first Muze charts.

Reclaim Data Sovereignty for the AI Era

For the modern IT leader, managing a hybrid cloud often feels like navigating a series of operational constraints rather than executing a strategy. You’re caught between the board’s demand for immediate AI results with disparate data silos, rising egress costs, inflexible consumption models, overworked employees, and the looming impact of hardware refresh cycles. There’s a constant friction between the agility of the cloud and the resilience of your on-premises core.

Hevo demo days: From Raw Data to AI-Ready: Build Live Pipelines in Minutes

Everyone is investing in AI, but most teams are blocked by one thing: their data isn’t ready. Data is scattered across SaaS tools, pipelines break silently, and insights are delayed. Without fresh, reliable, and centralized data, AI models, dashboards, and real-time use cases simply don’t work.

Ep 71 | AI Adoption: The Data Readiness Problem Holding Enterprises Back

AI ambition is everywhere. The models are ready, the investment is flowing, yet the outcomes aren’t keeping up. Cloudera’s Data Readiness Index 2026 survey identifies a widening gap between what enterprises want from AI and what they can actually deliver. In this episode of The AI Forecast, Paul Muller sits down with Cloudera CTO Sergio Gago to bring a practitioner’s lens to the problem, drawing on experience across the full spectrum from startups to global enterprises.

Data Products for Qlik Analytics - Datasets - The "Other" Tabs - Part 4

In part 4 of this series, Mike Tarallo form Qlik, walks you through the core components of Qlik Datasets, giving you a clear understanding of how to navigate and interpret key features within the platform. We explore the Profile tab, Data Lineage, Impact Analysis, and Data Preview to see how each helps you better understand your data and its flow across systems.

Proactive control through AI: NKT saves millions

NKT makes the “electrical superhighways” that bring renewable energy to city consumers. Its 24/7 site in Karlskrona, Sweden is the world’s largest producer of high voltage undersea cables, making operational stability vital. However, the plant faced hurdles. Data was trapped in silos, leading to intuition-based decisions with no single source of truth.

LIVE Build: Claude Code + Spotter | Agentic AI Meets Your Analytics Stack

Where agentic AI meets your analytics stack to drive action at scale. The shift is here. As the industry moves from Generative AI (Chat) to Agentic AI (Action), the pressure is on for developers and data practitioners to design intelligent apps that don't just talk: they perform. The real challenge? Bridging the gap between sophisticated developer tooling and your enterprise analytics stack. That’s exactly what this session solves.