US

Data warehouse for bank

  • 15

    15 integrated reporting systems

  • data warehouse for bank partnership

    Partnership with the International Advisory Services Frankfurt School of finance and management

  • data warehouse for bank implementation

    Implemented a liquidity risk management system for cooperation with the European Bank for reconstruction and development

Project overview

A data warehouse was implemented to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system, which is built for data analysis and reporting. It is a blend of technologies and components which aids the strategic use of data. It is the storage of a large amount of information by a business that is designed for query and analysis. It is a process of transforming data into information and making it available to users.

Advanced data warehouse with a reliable architecture that delivers an efficient workflow and information reliability thanks to automated processes. This solution provides consistent real-time control and analysis of significant bank operations.

Client information

Under NDA

logo nda-1

Business challenge

There was a strong need to verify the information from the reports, clarify the business needs about the reporting systems, and improve the data warehouse architecture to reach a smooth and consistent workflow.

The challenge was to develop and integrate a data warehouse, to implement a liquidity risk management system for cooperation with the European Bank for Reconstruction and Development. The final goal was to get a “golden source” and develop the main analytical and reporting dashboards.

Technical challenges

In a very short period, we had to build a new design for data warehouse architecture, the managerial reporting system. The challenge was to develop ETL processes for extracting, transforming, and loading the data from the 15 source systems to a warehouse.

Solution delivered

We have developed and implemented a process of regular control and analysis of the core banking operations based on Oracle UBS FLEXCUBE in partnership with the International Advisory Services Frankfurt School of Finance & Management. We built a data warehouse with 15 integrated systems, reporting systems for credit and deposit portfolios. We run multiple tests and delivered the project on time.

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Key features

data warehouse for bank key feacher-2

  • Advanced DWH

    A comprehensive data warehouse was built and based on the own information model with the data marts for all the operational workflow of the bank.

  • Bank-specific business measures

    BI deliverables include improved risk review model, better credit scoring, and customer segmentation.

  • Improved business processes

    They resulted in reduced load on commercial transaction systems and paved the way for optimized integrations.

  • Multi-level reports

    A new multi-level reporting system is based on Oracle BI, and it provides the opportunity to track each operation and transaction.

  • User-friendly interface

    Consistent and unified information source for scalable and reliable reporting. An interface provides users with easy-to-navigate elements.

Value to our client

  • 15

    integrated source systems. These tools provide extra functionality, including robust reporting dashboards and BI deliverables.

  • New

    data model for the deep analysis, strategical planning, forecasting.

  • The main data

    “golden source”.

Our tech stack

  • pl-sql PL/SQL
  • 1521204874 Oracle Apex
  • Oracle SQL Developer-Logo.wine Oracle SQL Developer
  • Git-Icon-1788C Git
  • jira-1 Jira
  • 480px-MS Project Logo Microsoft Project

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    Case study
    Data warehouse for bank
    diceus.com
    Case study
    Data warehouse for bank
    Project overview
    A data warehouse was implemented to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system, which is built for data analysis and reporting. It is a blend of technologies and components which aids the strategic use of data. It is the storage of a large amount of information by a business that is designed for query and analysis. It is a process of transforming data into information and making it available to users.

    Advanced data warehouse with a reliable architecture that delivers an efficient workflow and information reliability thanks to automated processes. This solution provides consistent real-time control and analysis of significant bank operations.
    Client information

    Under NDA

    Information
    Business challenge

    There was a strong need to verify the information from the reports, clarify the business needs about the reporting systems, and improve the data warehouse architecture to reach a smooth and consistent workflow.

    The challenge was to develop and integrate a data warehouse, to implement a liquidity risk management system for cooperation with the European Bank for Reconstruction and Development. The final goal was to get a “golden source” and develop the main analytical and reporting dashboards.

    Technical challenges

    In a very short period, we had to build a new design for data warehouse architecture, the managerial reporting system. The challenge was to develop ETL processes for extracting, transforming, and loading the data from the 15 source systems to a warehouse.

    Solution delivered

    We have developed and implemented a process of regular control and analysis of the core banking operations based on Oracle UBS FLEXCUBE in partnership with the International Advisory Services Frankfurt School of Finance & Management. We built a data warehouse with 15 integrated systems, reporting systems for credit and deposit portfolios. We run multiple tests and delivered the project on time.

    Key features
    • Advanced DWH

      A comprehensive data warehouse was built and based on the own information model with the data marts for all the operational workflow of the bank.

    • Bank-specific business measures

      BI deliverables include improved risk review model, better credit scoring, and customer segmentation.

    • Improved business processes

      They resulted in reduced load on commercial transaction systems and paved the way for optimized integrations.

    • Multi-level reports

      A new multi-level reporting system is based on Oracle BI, and it provides the opportunity to track each operation and transaction.

    • User-friendly interface

      Consistent and unified information source for scalable and reliable reporting. An interface provides users with easy-to-navigate elements.

    Value to our client
    • 15

      integrated source systems. These tools provide extra functionality, including robust reporting dashboards and BI deliverables.

    • New

      data model for the deep analysis, strategical planning, forecasting.

    • The main data

      “golden source”.

    Tech stack used in project
    • PL/SQL
    • Oracle Apex
    • Oracle SQL Developer
    • Git
    • Jira
    • Microsoft Project
    diceus.com