DWH project

Client Description

Sberbank Hungary was the Hungarian subsidiary of the international Sberbank Group, providing banking services for both retail and corporate clients. Its activities included lending, account management, and offering various savings and investment products. It operated under the ownership of the Russian parent company and aimed to provide innovative, customer-focused financial solutions in the Hungarian market.

Project General Description

Our large-scale data warehouse (DWH) and data mart development project in the banking sector aimed to fully modernize the institution's data management processes. This complex task included supporting critical business analytics, optimizing data loading procedures, and successfully integrating multiple source systems into the data warehouse. Throughout the project, we worked closely with the bank's internal DWH team to ensure faster and more efficient real-time data processing. This comprehensive development significantly improved the bank's decision-making processes, enabling quicker and more accurate business analytics.

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Banking, Financial, and Insurance Sectors
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Risk Management
 / 
Controlling
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Accounting
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Treasury
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RWO

Challenge

One of the biggest challenges was the rapid understanding and integration of new source systems into the data warehouse. This process required significant expertise and flexibility from our team. To ensure successful integration, we conducted detailed analyses of each source system, identifying their unique characteristics and data structures.

The efficient development of ETL (Extract, Transform, Load) procedures was crucial to the success of the project.

Additionally, we had to ensure the accurate scheduling and optimization of data loads within the system. Throughout the project, developing the appropriate data structures required close collaboration with business analyst teams to precisely meet reporting requirements.

How we helped?

  • Design Phase
  • Designing data structures and integration processes. Detailed mapping of business requirements.
  • Data Warehouse Loaders Implementation
  • Creating and establishing data warehouse loaders for each logically related unit of data. The development of ETL (Extract, Transform, Load) processes ensures the efficient and reliable loading of data into the data warehouse. We implemented daily data refresh mechanisms to provide up-to-date information.
  • Complete Data Mart and Reporting
  • Designing and establishing a data mart based on requirements.
  • Improving Decision-Making Processes
  • As a result of our work, data accessibility and processing speed improved significantly, which had a direct positive impact on the bank's decision-making processes.
  • Professional Support and Knowledge Transfer
  • Throughout the entire development cycle, we provided exceptional professional support to the bank's internal teams, which was crucial in maintaining the project's effectiveness and quality at a high level. This support encompassed not only technical issues but also included the transfer of best practices and ongoing knowledge sharing.
  • IBM DB2
  • DataStage