Daily data loading took up to 15 hours, delaying reporting and analytics. CALIGO implemented a fully automated, dependency-driven pipeline cutting load time to 3 hours — an 80% improvement — with centralised monitoring and Vertica-powered query acceleration.
Daily data loading processes were taking up to 15 hours, delaying data availability for reporting and analytics. Limited monitoring and fragmented process visibility made it difficult to track executions, identify bottlenecks, and respond to failures efficiently. Existing reporting workloads also struggled with performance under large data volumes.
CALIGO implemented a fully automated, end-to-end data loading framework orchestrated via Oracle Data Integrator, seamlessly transferring curated data from the Oracle PROD layer to Vertica through IBM DataStage. Centralised log and dependency management tables enabled a dependency-driven, monitorable execution model with full visibility into job execution. The entire data pipeline is automated, traceable, and efficiently managed end-to-end.
Daily data loading time reduced from 15 hours to 3 hours — an 80% improvement. Centralised logging simplified operations by enabling faster issue detection and resolution. With reporting workloads on Vertica, query performance improved substantially, allowing business users to access insights much more quickly and reliably.