Systems | Development | Analytics | API | Testing

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.

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.

Join Ouadie Limouni and Mike Tarallo on this week's Qlik Live Stream Friday for a look at Choose Your Champion 2026, an interactive World Cup prediction experience powered by. Ouadie will walk through the application, highlighting how machine learning, interactive analytics, and conversational were combined to create a unique fan experience for World Cup 2026 predictions.

Struggling to get clear, reproducible insights from petabytes of data? Join Charu Anchlia, Principal Engineer II at Cloudera, to see how Cloudera Agent Studio brings business users and tech analysts together under one simple interface. See how multi-agent orchestration—using specialized SQL and coding agents—can solve complex data analysis challenges, generate real-time visualizations, and seamlessly transform LLM outputs into repeatable Airflow pipelines.

The secret to a seamless customer experience? Embedding your intelligence. Ligentia wanted one consistent, branded experience across their entire supply chain offer. The fix? Partnering with ThoughtSpot. Catch Ligentia CIO Boris R. and Cindi Howson on podcast discussing how to turn standard apps into data powerhouses. Music: “The Clermont” by Flash Fluharty Licensed via PremiumBeat, ID: P9IHFMDYNZCKLEFZ.

The fastest way to AI might not be adding more tools. It might be getting more value from the data you already have. Discover how Cloudera optimizes your cloud infrastructure costs without disrupting your running business applications. This framework drastically lowers your data preparation and data readiness overhead while giving your teams total flexibility to use the analytics tools of their choice.

Every product team wants smarter analytics and AI. But for organizations that operate on-premises, in a hybrid-cloud environment, or regulated industries that can’t share protected data on the cloud, this forces them to either migrate or leave intelligence features behind. Can you access advanced analytics features without being boxed into a vendor’s cloud environment? Watch our video to learn: How to access analytics without compromise About tailored analytics experiences in a single platform.

Even if you can see exactly what is wrong with your data platform. Why is none of it getting fixed? A 30-minute conversation on closing the gap between what your dashboards see and what your team can actually get done, across Databricks, Snowflake, and BigQuery. Why it matters Most data teams are not short on insight anymore. The dashboards are full. Cost reports flag cost overruns. Observability platforms catch infrastructure misallocations. New AI assistants will even draft query rewrites for you.

For decades, network teams have been forced to choose between speed and stability. AI may finally be changing that equation. In this episode of The AI Forecast, Paul Muller sits down with John Capobianco, Head of AI and Developer Relations at Itential and author of “Automate Your Network,” to explore how AI is reshaping the future of network operations. Drawing on decades of experience in network engineering, John explains why network automation has struggled to gain traction and how AI, agents, and Model Context Protocol (MCP) could finally break the bottleneck.