Migration of On-Premise SQL Server EDW to Databricks Lakehouse on Azure for a Leading Financial Firm

Executive Summary:

VerticalServe, a top-tier consulting company specializing in data and analytics, was engaged by a leading financial firm to facilitate their migration from an on-premise SQL Server Enterprise Data Warehouse (EDW) to a more scalable, efficient, and cost-effective solution using Databricks Lakehouse on Azure.

The project involved the design and implementation of historical and incremental data pipelines to enable seamless data migration and ensure data integrity, security, and regulatory compliance. This case study outlines the approach, challenges, and outcomes of the migration project.

1. Company Background:

The client is a leading financial firm with a strong presence in investment banking, wealth management, and retail banking. They rely on their data warehouse to provide critical insights for risk management, fraud detection, and regulatory reporting. Their on-premise SQL Server EDW was struggling to scale with the increasing data volumes and performance demands.

2. Project Objectives:

The key objectives of the project were to:

• Migrate the existing on-premise SQL Server EDW to Databricks Lakehouse on Azure.
• Design and implement historical and incremental data pipelines for seamless data migration.
• Improve scalability, performance, and cost-efficiency of the data platform.
• Ensure data security, integrity, and regulatory compliance.

3. Approach:

VerticalServe utilized a phased approach for the migration project, which involved the following key steps:

• Assessment: Analyzed the client’s existing EDW architecture, data sources, and requirements to develop a migration strategy.
• Data Lake Design: Designed a Databricks Lakehouse on Azure, incorporating best practices for data storage, access, and governance.
• Data Pipeline Development: Developed historical and incremental data pipelines using Azure Data Factory and Databricks Delta for seamless data ingestion, transformation, and loading.
• Data Validation and Testing: Performed comprehensive data validation and testing to ensure data integrity and accuracy during migration.
• Security and Compliance: Implemented data encryption, access controls, and monitoring to comply with regulatory requirements and secure sensitive data.
• Knowledge Transfer: Provided training and documentation to the client’s IT team for ongoing management and support.

4. Challenges:

• Ensuring minimal downtime and business disruption during migration.
• Handling large volumes of historical data and optimizing the data pipelines for efficient data processing.
• Meeting strict regulatory requirements and maintaining data security.

5. Outcomes:

The successful migration to Databricks Lakehouse on Azure delivered the following benefits to the client:

• Improved scalability and performance, enabling faster query execution and data analysis.
• Reduced infrastructure and maintenance costs by leveraging Azure’s pay-as-you-go pricing model.
• Enhanced security and compliance with industry-specific regulations.
• Enabled advanced analytics capabilities with Databricks, leading to better insights and decision-making.
• Streamlined data management and governance processes.

6. Conclusion:

The migration of the on-premise SQL Server EDW to Databricks Lakehouse on Azure, implemented by VerticalServe, has provided the client with a scalable, high-performance, and cost-effective data platform. The historical and incremental data pipelines designed by VerticalServe ensured seamless data migration while maintaining data integrity, security, and regulatory compliance. The project has successfully met its objectives, delivering significant business value to the client.

About:

VerticalServe Inc — Niche Cloud, Data & AI/ML Premier Consulting Company, Partnered with Google Cloud, Confluent, AWS, Azure…50+ Customers and many success stories..

Website: http://www.VerticalServe.com

Contact: contact@verticalserve.com

Successful Case Studies: http://verticalserve.com/success-stories.html

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