When I talk to customers about privacy and their data, the topic is data sovereignty. More and more organisations want their data to stay in a specific jurisdiction, with no transfer to, or access from, another region. A few years ago, this was something for lawyers and compliance teams to worry about. Now it is a regular item on the C-suite agenda because it touches cloud strategy, innovation projects, and how you run the business day to day.

We are excited to announce that Confluent has entered into a definitive agreement to be acquired by IBM. After the transaction is closed (subject to customary closing conditions and regulatory approvals), together, IBM and Confluent will aim to provide a platform that unifies the world’s largest enterprises, unlocking data for cloud/microservices, accelerating time-to-value, and building the real-time data foundation required to scale AI across every organization.

Snowflake Intelligence brings enterprise insights to every employee’s fingertips, helping users answer complex questions in natural language with their own personalized enterprise intelligence agent. But for these agents to deliver truly accurate, contextually aware results within Snowflake’s Cortex framework, they need more than access to static or batch data—they need a continuous, trustworthy view of everything happening across the business right now.

Finance teams are smart, but not infallible. Even the most talented and dedicated finance professionals, like the ones on your team, are bound to make a mistake from time to time. But some mistakes are more costly than others. Have you ever been in the middle of a presentation and realized that you were talking about the wrong data? Or have you had an executive ask for data that you simply couldn’t find? With the right tools and automation, you can avoid these embarrassing moments.

For years, virtualization quietly powered the world’s digital infrastructure. Enterprises and government agencies relied on trusted platforms to keep workloads stable, secure, and efficient. But now, the landscape is rapidly shifting. Organizations are now looking for new capabilities in a virtualization platform, according to a new report by Red Hat, with 38% of companies desiring automation and AI-powered capabilities, and an anticipated 45% rise in the use of containers.

When we talk about JSON schema in the world of Kafka and streaming, you may assume the schema for the events/messages. But how many times have you fumbled in the configuration about trying to get an application deployed? Schemas that describe how to configure and deploy Applications or applications-as-code, are also important, allowing us to automate application landscapes. Especially as we will soon be a wash with catalogs for AI Agents, MCP servers etc.