Systems | Development | Analytics | API | Testing

Architectural Decision Guide: When to Use Apache Kafka (And When You Shouldn't)

Your team just shipped a microservices refactor. Services are smaller, deployments are faster, and boundaries are clearer. Then, during a design review, someone inevitably suggests: “We should use Kafka.”That suggestion might be the exact architectural breakthrough you need—or it could quietly introduce months of unnecessary operational complexity.This article serves as a practical decision framework.

Agentic Workflow for Petabyte-Scale Data Analytics | Cloudera Agent Studio

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.

Build Your Super Team: What 150 Years of Soccer Data Says

Soccer is a game of stories, but the most fascinating stories are often buried deep inside the numbers. And this year on the world's biggest stage, the tournament has expanded by nearly 60% – traditional scouting reports and pundit hot-takes simply can't keep up with the sheer volume of new data. That’s why we’re looking at the tournament through a much wider lens.

Gallus Insights: From Dashboard Overload to Instant Answers

I had the distinct pleasure of hosting a Snowflake Summit ‘26 session with Agustin “Augie” Del Rio, CEO and Founder of Gallus Insights, an analytics platform tailored specifically for mortgage lenders. As we sat down to discuss the future of analytics, one core truth echoed throughout the room: the most ambitious AI goals live or die by the quality of the underlying data.

The Optimization Paradox

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.

Logi Symphony: "No-Compromise Embedded Analytics

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.

Inside NERSC at Berkeley Lab: How a DOE Office of Science User Facility Is Exploring ClearML for Scientific AI Workflows

NERSC, the mission high-performance computing center for the U.S. Department of Energy Office of Science, is using ClearML as part of the AI infrastructure stack for Perlmutter, the upcoming Doudna supercomputer, and the broader American Science Cloud. Here is a look at what they are exploring and why it matters for AI for science at scale.

How to Optimize Data Readiness & Data Prep Costs

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.

How Agentic AI is Rewriting the Rules of Global Trade

Explore how a global supply chain company turned its data platform into a customer-facing product designed to operate at the speed of disruption. Boris Rabkin, Chief Information Officer at Ligentia, shares how the company executed that shift through a deliberate phased approach and a partnership with ThoughtSpot. He breaks down how to build a data foundation that scales, what it takes to embed analytics where decisions happen, and how to structure AI ownership and governance across a global regulatory environment.