Systems | Development | Analytics | API | Testing

How AI Transforms Retail, Finance and Manufacturing in 2026

In this episode, Dana Gardner sits down with three industry experts from Snowflake: Rosemary DeAragon, Rinesh Patel, and Tim Long to explore how AI will transform retail, financial services, and global manufacturing in 2026. Together, they break down the forces reshaping consumer behavior, enterprise operations, and competitive dynamics across these sectors. Across all three industries, one theme is clear: in 2026, AI will no longer be a side experiment. It will be a foundational driver of growth, efficiency, and competitive advantage.

Architecture Diagramming: From L0 to Ln - Simplifying for Every Audience #WordsUnplugged

Architecture diagrams are crucial, but the complexity of modern systems demands a better way to communicate. WSO2 CTO *Asanka Abeysinghe* and Lead Solutions Engineer *Erandi Ganepola* break down the L0-Ln Methodology—a simplified, level-based approach to visual abstraction. Watch our Words Unplugged video to discover how this scales from a team view to an organization-wide enterprise architecture, providing durable anchors (L0) and change-friendly details (L1-Ln) that evolve with the business.

How to Test Your React Frontend When the Backend Is Offline #speedscale #frontend #backend #coding

Software development is hard, especially when you have to ensure every component works together; it's an integration maze! And running a full stack (like React, Go, and Postgres) on your dev machine often means one thing: running out of memory! The Fix: We'll show you how to use Proxymock to record your components, effectively letting you run the frontend (or any component) completely isolated.

Streamline Code Testing with Proxymock

Tired of complex setups and running out of memory just to test one component? Learn how to use Proxymock (a FREE tool) to solve your biggest testing headache: component isolation! This demo shows you how to record and mock interactions across a complex React, Golang, and PostgreSQL stack, allowing you to find bugs before they ever hit production. In This Demo: This strategy lets you easily isolate components, simulate customer behavior, and ensure quality with lightning-fast local testing.

The $11 Billion Question: What the acquisition of Confluent by IBM means

What’s remarkable is how long Confluent competed at the highest level. Creating a category and type of application is hard; transitioning to cloud and surviving against hyper scalers is even harder. That alone is a huge achievement. Some see this as a pressured exit. But another way to look at it is as a strategic purchase by IBM to strengthen its position in enterprise data movement and integration.

A New Look for the Next Era of Analytics | ThoughtSpot Brand Update

We're defining the next era of analytics with a bold new look. This new brand identity is a visual representation of our vision, our product, and the way we show up for our customers: clear, confident, and built for what comes next. Because at ThoughtSpot, we know that analytics is not a destination—it's a system of action. This is Agentic Analytics. This is ThoughtSpot.

Cloudera Account 360: New Self-Service Administrative Platform Demo

Cloudera Account 360 is designed to resolve this by providing a single pane of glass from which customers can manage their users and accounts. It offers robust, flexible, and secure account as well as user management capabilities, helping you avoid delays by eliminating the need to raise support cases with Cloudera for simple administrative tasks. Foundational Features Available Now Cloudera Account 360 includes two core feature sets.

Inside ClearML's AMD Instinct GPU Partitioning Integration: Architecture, Orchestration, and Resource Management

GPU underutilization costs enterprises millions annually, with expensive accelerators frequently running single workloads at a fraction of their capacity. According to ClearML’s 2025-2026 State of AI Infrastructure at Scale report, almost half (49.2%) of IT leaders at F1000 companies identified maximizing GPU efficiency across existing hardware, including shared compute and fractional GPUs, as their top priority for expanding AI infrastructure over the next 12-18 months.