Systems | Development | Analytics | API | Testing

How Automating Marketing Data with AI Saves Hours

Did you know Cloudera's marketing operations team is using AI to automate workflows and eliminate manual processes? In this video, Kelly Sutter shares how Cloudera empowers marketing teams to unify data, uncover customer insights faster, and optimize marketing analytics with trusted enterprise AI. Discover how bringing AI to your data makes marketing more connected, responsive, and effective.

Why SAP HANA Resilience Matters as Much as Scale

SAP environments are built to support the business as it grows. Hitachi Vantara’s Virtual Storage Platform One (VSP One) Block High End is certified by SAP to support up to 1,008 SAP HANA nodes. That certification gives organizations a validated benchmark for the scale the platform can support, providing greater confidence as they consolidate, modernize and grow large SAP environments. But scale is only part of what mission-critical SAP systems require.

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.

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.

From Recommendation to Action: Scaling Autonomous Databricks Optimization in the Enterprise

Every Databricks optimization platform can tell you what should change. The harder question is: when should a system be trusted to make that change on its own? This session follows the journey of an Unravel customer as we moved from surfacing Databricks platform optimization recommendations to safely applying them in production. Prajakta will talk about the engineering decisions, the guardrails, and the trust model that made autonomous optimization possible in an environment where every change carries operational risk.

AgentSpot for Finance - Automating Lease Accounting Agent

Discover what’s possible with AgentSpot as Sheila showcases an AI agent ("Leasey") built to automate lease accounting. From analyzing contracts to creating calculations, schedules, and audit documentation, this workflow shows how teams can use agents to streamline everyday business processes. 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.

Raising the Stakes for Sustainable, AI-ready Infrastructure

Recent headlines are impossible to ignore. AI adoption is driving an enormous surge in demand for energy to power data centers and the storage systems operating within them. Energy constraints have become a primary bottleneck for data center development, with long grid connection queues and capacity backlogs.

Jedify CEO On Building Enterprise AI That Understands Your Business

Assaf Henkin, Co-Founder and CEO of Jedify, joins the Snowflake Summit 2026 News Desk to discuss how enterprises can build AI applications that truly understand their business context. Drawing from 15 years of experience building open source intelligence platforms, Henkin shares insights on balancing innovation with operations, staying true to founding principles while adapting to market changes, and how Snowflake's AI Data Cloud is enabling Jedify to reach new heights in the agentic AI era. Learn what's driving enterprise AI adoption and what founders should focus on for the back half of 2026.