Challenge

The bank’s legacy data platform was no longer fit for purpose. Built on an end of life Oracle BDA system, it lacked vendor support and an upgrade path.

Metadata complexity had increased significantly, with over 400,000 tables in a single schema due to inefficient backup design.

Performance constraints were severe. Query execution took up to 8 minutes, while batch ingestion cycles ran monthly or yearly, delaying data availability.

Reporting processes were manual and dependent on CSV and Excel workflows, with no real time visibility.

Solution

Digile implemented a cloud ready lakehouse using DigileEdge to modernize the platform.

The new architecture simplified data pipelines, reduced metadata complexity, and improved processing speed at scale. Automation and self healing capabilities enhanced reliability and minimized manual effort.

Curated datasets and real time access enabled faster and more effective data consumption.

The solution included:

• Implementation of a Kubernetes-native data platform
• Integration of Change Data Capture (CDC) using Striim
• Enablement of real-time data streaming and processing
• Unified data governance and observability framework
• Optimization of infrastructure to reduce operational overheads
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Technology Used

• DigileEdge
• Data lakehouse architecture
• Open standard technologies
• Automated data pipelines

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