As you wrap up Cybersecurity Awareness Month, take a moment to think about what defense and compliance really share; protecting data you can trust and proving it when it counts. It’s also important to remember that if that data gets called into question, nobody cares what the slide deck says. They care what the system that stores it can prove. That makes it essential to have data infrastructure that can back it up.

Every business uses its own unique stack of tools to run marketing, sales, customer support, finance, operations, and more. And while each tool plays an important role, the data they generate stays spread across systems that don’t “talk” to each other well: While Databox already connects to 130+ of the most popular tools, some teams need access to a broader range of integrations and more flexibility to prepare their data for analysis.

If 2024 was the year enterprises adopted Generative AI, 2025 is the year Agentic AI became a reality. In the last six months, the conversations I’m having with engineering leaders have quickly shifted from simple chatbots to AI-enabled IDEs, copilots and autonomous systems that take action. This has to a large part been helped thanks to MCP. To date there have been 10,000+ MCP integrations built by the community, so to say it is a success is an understatement.

Your teams don’t buy features; they buy outcomes. Speed to insight, trusted AI, lower TCO. That’s the lens for our Qlik Product Recap, a curated view of what’s new across Qlik and why it matters. We loved meeting many of you at Qlik Connect, and you’ll see several features we highlighted there plus everything we’ve shipped since, organized by the outcomes they enable. While Qlik Connect is a great moment to showcase innovation, it’s only one waypoint.

As a product manager, you want analytics that add value without adding complexity. Automated insights do the heavy lifting inside your app, surfacing key changes for your users without making them dig. The result is happier customers, fewer support tickets, and more time for you to focus on roadmap and innovation.

Migrating from self-managed Apache Kafka connectors to fully managed connectors has been a persistent challenge for data teams working on Confluent Cloud. While Confluent-managed connectors deliver enterprise-grade features, seamless upgrades, and comprehensive support that add up to significant development and operations cost savings, the journey to get there often feels daunting and opaque.