Systems | Development | Analytics | API | Testing

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.

Learn how to build an end-to-end, real-time edge-to-AI data pipeline to tackle critical enterprise challenges like credit card fraud detection. In this demo, Diby Malakar (Product Lead for Data in Motion) demonstrates how to process an average of 5,000 transactions per second in low hundreds of milliseconds to detect fraud instantly. Discover how Cloudera’s Data in Motion suite enables application developers to ingest, govern, and enrich streaming edge data to power instant AI model inference and live analytics.

Stop burning budgets on AI for AI's sake. With billions pouring into data centers, many enterprises are experiencing massive buyer's remorse. How do you ensure your company is part of the 10% actually driving results? Guest Mark Ritcey breaks down.

If an AI agent gives a business user the wrong number, and a consequential decision gets made off it, who's responsible? The data analyst who built the semantic layer? The platform? Or the business user who asked the question and acted on the answer?

See how AI agents use Model Context Protocol (MCP) with FME to connect complex enterprise and spatial data to Snowflake. In this episode of Do It Better with Snowflake, Safe Software CEO Don Murray demonstrates how FME extends Snowflake Cortex AI Agents with FME workflows for data integration, transformation, and spatial analysis. See how Snowflake + FME can help you: Connect complex data: including GIS, CAD, 3D, LiDAR, BIM, ERP, and unstructured data.

Traditional dashboards and static reports are not built around the person reading them. In this video, we introduce Data Apps in AgentSpot, a new surface alongside Agents and Workflows, and walk through a Used Car Lot Operations App built for a regional dealership manager. It pulls from ThoughtSpot data models and Slack conversations into a single narrative, scopes every app to the viewer's own credentials so people only see the data they have access to, and supports real interactivity like KPI card drill downs, custom filters, and what if pricing analysis.

The August Snow Report is LIVE Two GA launches for CoCo, warehouse tuning that handles itself, and World Tour in 23 cities. What's new CoCo Desktop is GA A native IDE inside your governed Snowflake environment, so it knows your data models and access policies from day one. Up to 2X faster on complex tasks with 51% fewer tokens than third-party assistants. Cloud Agents are GA Run agentic workflows from your browser in Snowsight. Start with a prompt, close your session, and the agent keeps working on Snowflake's managed infrastructure.