Raw data from IoT devices, like GPS trackers or electronic logging devices (ELDs), often lacks meaning on its own. However, if combined with information from other business systems, such as inventory management or customer relationship management (CRM), this data can now provide a richer, more complete picture for more effective decision-making. For example, combining GPS data with inventory levels can optimize logistics and delivery routes.

In today's data-driven world, staying ahead means acting on the most up-to-date information. That's where change data capture (CDC) comes in. CDC is a design pattern that tracks your database tables, capturing every row-level insert, update, and delete as it happens. This real-time monitoring allows downstream systems to react to changes instantly, without batch-based updates and resource-intensive full scans.

We are proud to announce the release of Apache Kafka 3.9.0. This is a major release, the final one in the 3.x line. This will also be the final major release to feature the deprecated Apache ZooKeeper mode. Starting in 4.0 and later, Kafka will always run without ZooKeeper.

A year in at Confluent, Product Manager Surabhi Singh has learned a lot about data streaming—and even more about herself. In this fast-paced environment, Surabhi is highly motivated and committed to her work strategically planning, coordinating, and delivering product improvements for customers whose business operations depend on Confluent Platform.