Data Ingestion: Data enters the cassandra system through batch loading, and real-time streaming through message queues.

Cassandra Cluster: Serves as the central data store, supporting both OLTP (real-time read/write operations) and OLAP (analytical processing) with data replication for high availability.

Real-Time Analytics: Applications and dashboards provide real-time analytics using data from the Cassandra cluster.

Batch Processing: Data is processed in batches with tools like Spark SQL, Spark R, and MLlib, and results are stored in an analytical deep layer.

Integration with BI Tools and Data Science: The architecture supports both real-time data access and batch processing for BI tools and data science workflows.