Case Study

A Successful Migration from On-premises Hadoop to Databricks

A global bank harnesses Azure Cloud and Databricks for digital transformation

A leading bank achieves digital transformation at a global scale by moving its legacy on-premises Hadoop infrastructure to the Azure Cloud and leverages Databricks to democratize data and advance its AI capabilities.
Industry & Region: Banking and Financial Services, Global

Technology Stack: Cloud Data Platform: Azure, Data Platform: Databricks Data Intelligence Platform, Optimized Data Storage Framework: Delta Lake, Data Visualization: PowerBI, Machine Learning Platform: MLflow

Client Overview
Our client is a global bank committed to leveraging the latest technologies for data-driven innovation, streamlined workflows, and improved process efficiencies.
Business Challenge

The bank aspired to deliver its customers a truly digital banking experience. However, its legacy infrastructure and data warehouses on the on-premises Hadoop system were impacting this larger business goal. Leveraging the full potential of the large volumes of data, that they generated across hundreds of disparate source systems, became a challenge. The traditional setup presented data access complications and created data silos. This resulted in siloed data insights and best practices across the global teams working in isolation, impacting innovation at scale. Overall, the inefficient data processes and workflows slowed down business operations and the go-to-market capabilities of the bank.

Solution Offered
Our team of experts, on evaluating the pain points and the core business objective of a holistic digital transformation, came to a consensus that a domain-driven data lakehouse and a data mesh approach would be the right solution.

As a first step, we moved the traditional Hadoop system to the Azure cloud. This transition to Azure not only brought unparalleled scalability but also set the stage to harness the Databricks Data Intelligence Platform for its advanced analytics and other capabilities.

Databricks Data Intelligence Platform unified data from multiple sources into a single platform. It created a collaborative environment for data engineers, scientists, and analysts. The fast and reliable data pipelines built using Delta Lake enabled access to high-quality data critical for accurate insights and model training.

The new platform was seamlessly integrated with PowerBI to enable data analysts to visualize and transform data and use it for business reporting.
Additionally, MLflow was connected to allow the data scientists and ML engineers to automate the deployment of ML models into production and eliminate inefficient manual processes.
Value Delivered
  • A collaborative platform for seamless sharing of data insights.
  • Accelerated ML adoption for data-driven decision-making.
  • Enabled accurate product recommendations for improved customer satisfaction and reduced customer churn.
  • Enhanced risk management and threat detection through the identification of anomalous patterns.
  • Simplified infrastructure management.
Want to know how migrating your legacy Hadoop systems to modern cloud-based platforms like Microsoft Azure and Databricks can help you leverage your enterprise data more efficiently?

A Successful Migration from On-premises Hadoop to Databricks