Building healthcare AI without rebuilding your data platform
To fully take advantage of AI, your organization needs a solid foundation of automated data integration, context engineering, and an agentic harness.
Qlik Declarative Pipelines with AI and VS Code
Managing your data pipelines shouldn't mean leaving the tools you already work in. In this video, Qlik Solution Architect, Joe Easley, shows how Qlik's declarative pipelines let you build and manage your integration ecosystem right alongside your own LLM and IDE — no switching platforms, no extra UI to learn. The benefit: faster iteration, fewer handoffs, and pipelines that live where your code already does.
The Only 2 things that will set you apart in the AI Era
In a world where knowledge, experience, and even intelligence are no longer barriers, what actually separates the people who thrive from everyone else? In this conversation, we get into the two traits that matter more — curiosity and agency, and why they're becoming the real differentiators in the age of AI. "Today it's Models Day. Tomorrow it may be something else." The tools keep changing; the will to figure things out doesn't.
Zero-code, low-cost data ingestion: New BigQuery DTS capabilities
Discover new BigQuery Data Transfer Service capabilities. Automate low-cost data ingestion from diverse sources directly into your data warehouse.
What Is Agentic iPaaS? The Next Evolution of Integration Platforms
Traditional integration platforms were built for a world of predictable, human-configured workflows. But with enterprise software rapidly incorporating agentic AI capabilities, that world is changing fast. Agentic iPaaS represents a fundamental architectural shift where intelligent agents reason, adapt, and execute integrations autonomously, moving beyond simple "if-then" automation to goal-oriented systems that make real-time decisions.
How to Build a Self-Healing Data Pipeline with AI Agents (Step by Step)
Your data pipeline breaks at 2 AM. Again. By morning, corrupted data has cascaded through dashboards, reports sit empty, and your team spends half the day tracking down root causes instead of building features. This scenario plays out across organizations daily. Data engineers spend 44% of their time firefighting pipeline failures rather than delivering value.
Open Data Infrastructure needs context engineering to unify data use cases
A single source of truth doesn’t just come from centralizing data. You have to engineer context from it, too.
Bring AI to Your Data, From Prototype to Production | Cloudera AI Inference
Most enterprise AI projects stall when teams try to move experiments into production—where costs, governance, data security, and scale all get real. In this demo, see how Cloudera AI Inference helps turn foundation models into secure, governed, production-ready AI services. You’ll learn how to: Chapters: Subscribe to stay ahead of the curve with the latest in data strategy, open architectures, and enterprise AI innovations.
We built our own status page with AI, replacing a $65k SaaS product
Two engineers used AI coding agents to design, build, and ship a production-ready status page — here's what worked, what didn't, and what we'd do differently.
Agentic Future Ready With BigQuery: Continually Improving Price-Performance, Zero Effort
Learn about the latest innovations to help improve BigQuery price-performance with autonomous query processing.