Kafka and the Confluent platform are increasingly becoming central elements in big data architectures across diverse industries, functioning as a nervous system that integrates streaming and batch data for enhanced decision-making. This integration allows companies to process real-time data streams alongside historical data from traditional databases, providing context and enabling applications like fraud detection, real-time reporting, and healthcare analytics. Syncsort partners with Confluent to bridge the gap between these data types, demonstrating the benefits of this approach in various sectors. For instance, fraud detection systems can use real-time transaction data to identify and prevent fraudulent activities promptly, while hotels and healthcare providers can make more informed decisions by analyzing up-to-date data. The collaborative efforts of Syncsort and Confluent illustrate how combining batch and streaming data architectures can transform data processing, making it dynamic and responsive to real-time needs.