Finance

Migrating Legacy Data Warehouse from Oracle to SQL Server for a Financial Institution

Focus Areas

Data Integration

IT Infrastructure

Data Management

Business Problem

A major financial institution group’s outdated Oracle-based data warehouse was causing inefficiencies with operations and data processing times. As the volume of financial data grew, the system was becoming increasingly difficult to scale and maintain and impacted the institution with high operational costs, slow data processing times, and the generation of accurate and timely financial reports. The banks needed a modern, scalable solution that would reduce costs, enhance performance, and improve data access.

Key challenges:

  • Lack of Scalability: The institution’s ability to process and analyze large datasets was limited by the Oracle-based legacy data warehouse which could not scale effectively to accommodate the growing financial data.

  • High Operational Costs: Adapting the Oracle infrastructure to meet the bank’s data needs required significant resources and was especially expensive in terms of licensing and operational management. 

  • Slow Reporting Times: Lack of access to real-time data and the system’s limited processing power delayed financial reports and slowed down decision-making. It also negatively impacted the bank’s ability to meet regulatory deadlines.

  • Data Migration Complexity: The migration from Oracle to SQL server of a large volume of financial data posed several technical challenges, such as data integrity, compatibility, and performance considerations.

The Approach

Curate consultants carried out a thorough assessment of the bank’s current infrastructure and data workflows in collaboration with the internal IT, finance, and compliance teams. The team designed a solution that involved a strong migration strategy along with addressing the scalability and cost issues and integrating real-time data access and analytics tools.

Key components of the solution:

  • Discovery and Requirements Gathering:

    • Curate identified the following key requirements after working closely with the bank’s internal teams and assessing the Oracle infrastructure and its data processing workflows:

    • Move data from Oracle to SQL Server through a seamless migration strategy.

    • Ensure scalability, decrease costs, and improve processing power through cloud infrastructure.

    • Implement real-time reporting and data access features to enhance decision-making and stay compliant with regulations.

    • Minimize downtime and ensure data integrity during migration.

    Migration strategy using SQL Server Integration Services (SSIS): Curate efficiently transferred data from Oracle to SQL Server by designing a robust migration strategy utilizing SSIS.

    • Data Mapping and Transformation: SSIS packages were designed for the complex data mappings between Oracle and SQL Server. This included transforming data formats to ensure compatibility and restructuring datasets to fit the new environment.

    • Validation and Data Integrity: Validation steps were implemented within the SSIS packages to ensure the integrity and accuracy of data during the migration process. Automated data validation scripts were integrated to detect any inconsistencies between source and target systems. 

    • Incremental Data Migration: The incremental migration approach allowed the system to be completely operational while the migration was in progress by moving data in batches.

  • Cloud Integration and Infrastructure Optimization: Curate migrated the bank’s data storage and processing infrastructure to Azure to address scalability and cost issues.

    • Azure Data Storage: Azure Data Lake and Azure Blob Storage were used to store structured and unstructured financial data efficiently. Transitioning to Azure’s scalable cloud storage solutions ensured that the bank could handle increasing data volumes without performance issues. 

    • Scalable Processing: Azure SQL allowed for scalable and high-performance synchronous financial data processing and reduced the time needed to generate reports.

    • Reducing Costs with Cloud: Azure’s pay-as-you-go model eliminated the need for on-premise hardware maintenance and Oracle licensing fees, reducing infrastructure costs and allowing for dynamic adjustment of resources as needed.

  • Reporting and Analytics: Curate integrated analytics tools and real-time data access to improve the bank’s reporting abilities.

      • Power BI: To facilitate quicker, more informed decision-making, Power BI dashboards were integrated. These provided real-time insights into financial data and enabled decision-makers to access key financial metrics and reports instantly. 

      • SQL Server Reporting Services (SSRS): Curate automated the generation of regulatory and compliance reports through SSRS to ensure that the bank met reporting deadlines without delays. The automated reporting tools were directly integrated with the new SQL Server infrastructure for seamless data flow.

  • Stakeholder Engagement and Change Management: To ensure smooth implementation and minimal disruption, Curate worked closely with the bank’s internal teams and external vendors throughout the migration process.

    • Internal teams: To ensure that the migration strategy aligned with the institution’s business goals and regulatory requirements, Curate regularly engaged with the bank’s IT, finance, and compliance teams.

    • External Vendors: Curate collaborated with cloud service providers and software vendors and addressed any technical challenges that arose during the migration.

    • Change Management and Training: Curate provided comprehensive training, detailed documentation, and best practices to ensure the long-term success of the new SQL Server infrastructure and cloud services. 

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Business Outcomes

Decreased Operational Costs


By migrating to Azure and SQL Server, the bank reduced its infrastructure and licensing costs by 30%. It also helped to optimize resources based on demand, further driving down operational expenses.

Improved Data Scalability


The bank could handle large volumes of financial data without compromising its performance with Azure’s scalable infrastructure.

Real-time Reporting


The implementation of SSIS and real-time data processing helped the institution meet regulatory deadlines and improve decision-making. Financial reports were generated faster and more accurately, with reporting times being reduced by 60%.

Enhanced Data Integrity


Curate’s meticulous data migration strategy ensured that all data was transferred accurately. Automated validation and monitoring tools provided continuous assurance that the data migration was error-free.

Sample KPIs

Here’s a quick summary of the kinds of KPI’s and goals teams were working towards**:

Metric Before After Improvement
Data migration completion time 6 months 3 months 50% reduction
Financial report generation time 10 hours 4 hours 60% reduction
Infrastructure costs (annual) $500,000 $350,000 30% reduction
Scalability (data volume capacity) Limited Scalable (cloud) 100% improvement
Data validation errors 15 errors/month 1 errors/month 93% reduction
**Disclaimer: The set of KPI’s are for illustration only and do not reference any specific client data or actual results – they have been modified and anonymized to protect confidentiality and avoid disclosing client data.

List of skills, tools, and technologies

The following set of skills, resources, tools, and technologies were used:

  • Cloud Architects: Skilled in Azure infrastructure design, data storage optimization, and scalable cloud solutions.

  • Data Migration Specialists: Expertise in SSIS package development, data mapping, and large-scale data migration strategies.

  • Database Administrators: Proficient in managing Oracle and SQL Server environments, ensuring data integrity, and optimizing database performance.

  • Data Engineers: Experience in developing ETL pipelines, automating data transformation, and real-time data processing.

  • DevOps Engineers: Knowledgeable in deploying CI/CD pipelines and automating cloud infrastructure management.

  • Change Management Specialists: Skilled in training internal teams on new systems, managing transitions, and supporting operational continuity.

Tools & Technologies

  • Cloud Platforms: Microsoft Azure (Azure Data Lake, Azure Blob Storage, Azure SQL)

  • Data Migration & Integration: SQL Server Integration Services (SSIS), Oracle Data Integrator, Talend

  • Real-Time Reporting: Power BI, SQL Server Reporting Services (SSRS)

  • Data Validation & Automation: Python scripts for data validation, Azure Monitor for real-time monitoring

  • Performance Optimization: Azure SQL, SQL Profiler, Azure Performance Insights

  • Collaboration & Project Management: Jira, Confluence, Microsoft Teams

Conclusion

Curate provided the bank with a scalable, high-performance solution that decreased operating costs, increased data processing speed, and boosted reporting capabilities by using Azure’s cloud architecture to migrate the bank’s legacy data warehouse from Oracle to SQL Server. Data integrity was preserved during the transition thanks to the automated data migration approach, and system reliability with future data growth was assured by integrating scalable cloud infrastructure and real-time reporting. Curate’s ability to deliver tailored cloud and data migration solutions that drive operational efficiency and long-term business success helped ensure short and long-term system sustainability.

 

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