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Modernising EFL’s data warehouse solution to match their future needs

Taking the necessary actions to support EFL’s data strategy

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Case Study EFL Data Warehouse Modernisation Navy 800X400
Europejski Fundusz Leasingowy

EFL S.A.

EFL S.A. (Credit Agricole group) began its operations in June 1991 as one of the first leasing companies in Poland. Today, the company provides a comprehensive set of financial solutions, including lease, loan, long-term hire, factoring, and more. They serve more than 320,000 customers and have financed 65 billion PLN worth of investments.

Industry Financial Services, Leasing
Technology Data warehouse, Microsoft SQL Server, SQL Server Integration Services

Key Achievements

  • A future-proof data warehouse solution leveraging the latest technologies
  • Improved governance resulting in smooth data loading and better efficiency
  • Scalability and system integration allowing the solution to accommodate future business growth

The challenge

Business Need

As a large financial institution serving hundreds of thousands of customers, EFL needs a robust data solution to handle their operations. Their original data warehouse was no longer meeting these needs, as it was hosted on an outdated version of the Microsoft SQL Server. This contributed to multiple issues for the organisation.  

Most importantly, this old SQL version was no longer receiving technical support. EFL had to solve all the potential issues with the server on their own. Moreover, it lacked various improvements that were introduced in the later versions.  

The performance was also insufficient; the overnight processes often required more time than was acceptable for the client. This resulted in increased downtime and reduced customer satisfaction. At the same time, the old solution lacked crucial functionalities, which prevented further modernisation.   

As a result, the solution wasn’t cost efficient and required improvements in the aspects of security and performance. 

 

The solution

Project Details

The main goal of the project was to migrate EFL’s data warehouse to a significantly newer version of the Microsoft SQL Server. This, alongside the scale of the data warehouse and over 100 unparametrised SQL Server Integration Services (SSIS) packages, resulted in a high complexity of the project. There were no off-the-shelf solutions available on the market that were able to support such a large technology leap. Because of that, bespoke development was required.  

Objectivity created a tool to automate the package parametrisation process. This solution took care of the most labour-intensive part of the project. At the same time, the team prepared the data warehouse for the introduction of testing environments and DevOps pipelines to ensure full operability.  

Regressive testing and a parallel run period were employed to ensure a smooth transition of this business-critical system and all of its functionalities. EFL’s data architecture has been optimised, and the new data warehouse was seamlessly integrated with existing clients’ systems.  

The team also deleted the unnecessary connections between the data packages and cleaned up the SSIS solution’s structure to improve data governance.

The results

Business Benefits

The data migration was a complete success. After switching to the new SQL version, EFL received full support from Microsoft, including software updates, security assistance and bug fixes. Performance has improved significantly, and the overnight processes have been optimised. Technical debt was eliminated, and the improved governance contributed to the smooth data loading and increased efficiency of the solution.   

The critical issues affecting the previous data warehouse have been resolved. The solution has been adapted to modern standards and, thanks to these changes, the potential future adjustments can be made much more easily. The new solution is scalable and has been fully integrated with the existing systems. The data warehouse is now ready for setting up the testing environments and DevOps pipelines. This gives EFL the necessary confidence in their data architecture and enables future growth without having to worry about the limitations of their data warehouse. 

 

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