By integrating Apache Spark Streaming, the data freshness rate, and latency have significantly improved from 24-hour batch processing to less than one minute, facilitating faster communication to downstream systems, aiding marketing campaigns.
Apache Spark Streaming, known for its efficiency and stability, provides near real-time analytics with low latency data transformations. It is suitable for competitive intelligence and workflow monitoring, extending to machine learning in a low-code environment. However, improvements are needed in user configuration for better business user focus, and initial setup can be complex. While resource-intensive, integrating event-level streaming could enhance capabilities, despite challenges with memory management and latency for real-time analytics.
