Systems | Development | Analytics | API | Testing

Ready Set Code! The Telemetry Tsunami

Welcome to Ready Set Code! The game show where data engineers face off to prove who can build faster. In today's episode, "The Telemetry Tsunami," three contestants face a massive flood of nested JSON telemetry data. Their mission: flatten the arrays, join it to customer tables, and deploy a secure automated pipeline. Who will separate themselves as a data driver vs. a data downer? Find out now! Type Less. Build More.

The Hidden Cost of AI Testing: Stop Burning LLM Tokens in Your CI/CD Pipeline

AI testing against live LLM APIs can quietly drive massive token costs across development, QA, and CI/CD pipelines. Every test execution consumes real tokens—at production rates—creating hidden, variable costs that scale with your AI adoption. In this video, discover how leading enterprises are eliminating LLM token spend using service virtualization. Learn how BlazeMeter intercepts API calls, simulates realistic AI responses (completions, embeddings, and large payloads), and enables full-scale testing without invoking live models.

Streaming highlights from Databricks Data + AI Summit

Join Tun Shwe and Jeremy Frenay as they stream live from the floor of the Databricks Data + AI Summit! They’ll break down the biggest announcements, key takeaways, and cutting-edge trends shaping the intersection of AI and data streaming. Register to get an insider look at the future of data AI streaming.

The internal war over who owns AI.

There is a massive boardroom fight happening right now over who gets to control AI. Should it be IT? A centralized lab? The executives? Boris Rabkin from Ligentia drops a truth bomb: AI belongs wherever value is actually created. If your AI strategy is locked inside an isolated corporate lab instead of in the hands of your product, engineering, and customer teams, it’s going to fail. Full episode out now!

Reporting Intelligence UI Flyover

See how Reporting Intelligence from insightsoftware transforms the way finance teams build, manage, and distribute ERP-connected reports, without IT involvement, data engineering, or infrastructure overhead. This walkthrough covers the full product experience, from self-serve report building in Excel to cloud-based scheduling and distribution, embedded Lineos AI assistants, and the autonomous Intelligence Layer that monitors your KPIs and surfaces insights around the clock.

Ep 78 | Mastering Enterprise AI: Why Some Projects Succeed While Others Fail

AI may be the most capable intern your organization has ever hired. However, interns still need guidance and clear direction. Enterprise AI is proving no different. In this episode of The AI Forecast, Paul Muller sits down with Michael Gray, CTO of Thrive, to explore the patterns and anti-patterns emerging from real-world enterprise AI deployments. Drawing on his experience helping organizations implement AI at scale, Michael offers a practical framework for evaluating AI maturity, helping leaders understand where adoption breaks down and what it takes to build momentum across the organization.

Stop Rebuilding Data Models From Scratch: Meet SpotterModel

Your data engineering team shouldn't be the bottleneck between a business question and a governed answer. SpotterModel turns a natural language prompt into a deployable data model. This release does the heavy lifting on complex calculations, and lets you roll back to any previous model state, anytime, so a bad change never costs you hours of rebuilding. It maps your relationships, dimensions, and measures instantly, and you stay in control of table selection and the build process the whole way.