Case Study - Data Pipeline Modernization for a Leading Bank in the Middle East

antony melwin
Nov 6
2 min read

When Legacy Systems Delayed Payment Reconciliation

A major Middle Eastern bank relied on legacy SSIS-based ETL pipelines for payment reconciliation - and they were slowing down under growing data volumes. Payment data was delayed, job failures were common, and manual restarts created long reconciliation cycles.

Each delay had downstream effects: delayed reports, longer transaction closure times, and higher operational costs. Engineers were firefighting instead of innovating.

Objective:

Modernize the data platform for reliability, scalability, and predictable operating costs - without risking data loss or operational downtime.

WhiteBlue’s Approach and Solution Design

WhiteBlue proposed a two-phase data pipeline modernization roadmap using Azure Data Factory (ADF) and Azure Integration Runtime.

Stabilize first: Move existing SSIS packages “as-is” to Azure. This quick migration brought immediate performance improvements and centralized monitoring.

Then optimize: Re-engineer legacy ETL pipelines using native ADF components, improving scalability, cost governance, and transparency.

Key steps included:

Establishing monitoring through Azure Monitor and Cost Management to control cloud spend.
Introducing automated alerts to reduce manual intervention.
Integrating Azure Synapse Analytics and Databricks for analytics readiness.

This two-step method balanced risk, speed, and modernization depth - improving reliability while maintaining business continuity.

Data Pipeline Modernization Implementation Journey

The migration was executed incrementally to prevent disruptions. The first batch of pipelines was moved and monitored in a controlled pilot run. After stability was confirmed, the remaining workloads followed.

Parallel testing ensured data accuracy, and team training sessions enabled staff to manage new ADF workflows independently.