Systems | Development | Analytics | API | Testing

The dashboard looked perfect. It was AI-generated, visually stunning, the kind of output that would sail through a stakeholder review without a second glance. Then, during a live stream, someone pointed out the KPI in the top left corner was wrong. That moment captures one of the most important and underappreciated risks in AI-generated analytics right now. A confident answer isn't the same as a correct one, and in enterprise settings, the gap between the two can be very expensive.

The Thought Tank is back. This time, ThoughtSpot CMO and host Micheline Nijmeh is sitting down with Kelley Jarrett to unpack where Sales Ops gets an edge with real-time data. Join us live on August 26th at 12:30 PM ET. If you're in Sales Ops or RevOps, this one's for you. Kelley will pull back the curtain on how she actually runs pipeline, manages AE performance, and keeps forecast accuracy honest, all from ThoughtSpot.

Watch how AgentSpot builds a Product Discovery Agent that reads support tickets, sales calls, Slack threads, CRM notes and product analytics, clusters what customers keep raising into ranked themes, and hands your PMs the pattern, the accounts affected, the evidence behind it and what to do next. What is AgentSpot? AgentSpot is an Agentic Workforce Platform for building workflows that make decisions, take action, and deliver results across every system your business runs on, grounded in your data.

Watch how AgentSpot builds an Opportunity Planning Agent that reads your validation brief in Confluence, queries your GTM and product models in ThoughtSpot for the evidence behind it, weighs the build options against real pipeline and roadmap themes, and publishes a decision-ready brief with a named bet, a priority call, and a now-next-later path, so your next planning cycle starts from evidence instead of opinion.

Watch how AgentSpot builds a Release Notes workflow that checks GitHub every morning for new staging releases, gathers the merged PRs behind them, rewrites the whole lot into benefit-first, jargon-free release notes, and publishes them as a Slack Canvas with a short summary posted to your channel, so your team learns what shipped without anyone hand-writing it. What is AgentSpot? AgentSpot is an Agentic Workforce Platform for building workflows that make decisions, take action, and deliver results across every system your business runs on, grounded in your data.

Today’s enterprises face immense pressure: scaling fast, staying compliant, and unlocking AI-driven insights—all while fighting siloed data and growing cloud complexity. There is a better way forward, and it starts with Cloudera’s vision for the cloud experience anywhere. Cloudera is the only data and AI platform that delivers the cloud experience anywhere—public clouds, data centers, and the edge—bringing unified security, governance, and control to data wherever it resides. Access 100% of your data for AI-driven insights and future-proof—not just modernize–your enterprise data strategy.

Now that AI coding tools have put development capabilities into more hands, prototypes are becoming business-critical applications almost overnight. Shanea Leven sees an opportunity for a new generation of builders, provided the infrastructure around their applications keeps pace. Shanea explains how organizations can give developers and new technical employees room to build while maintaining the standards required for enterprise software..

Use Qlik Answers to manage and create your Data Products!

The challenge for most data teams isn’t a lack of ideas—it’s the time it takes to turn those ideas into something usable. In this session, Steffen Bischoff, Chief Architect Data at Qlik, follows a single dataset from a core system through its entire journey to becoming a governed data product. You’ll see pipelines created by describing intent instead of writing code, versioned in Git, then curated, quality-checked, and documented with the help of specialized agents. From there, the data product is made available to the AI tool of your choice through the Qlik MCP Server.

Semantic layers and ontologies have moved from nice-to-have data modeling tools to the foundational engine required for enterprise AI. In this episode, Raman Tallamraju, Senior Director and Head of Enterprise Data Architecture and Engineering at Vanguard, breaks down how Vanguard is architecting its AI semantic layer to turn scattered institutional knowledge into reliable, agent-ready context. He shares why autonomous agents expose decades of hidden data debt, how to bridge domain-specific definitions like clients versus prospects, and how to balance building a unified semantic layer with a pragmatic, federated data operating model.