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DWBI implementation leveraging reusable ETL components that helped minimize implementation time

DWBI implementation leveraging reusable ETL components that helped minimize implementation time

Client

Is one of the largest banks in Singapore and Malaysia.

Services Offered

DWBI Implementation

Domain

BFSI

Application Environment

Teradata, Teradata FSLDM, Teradata Queryman, ERWIN, Datastage, Sunopsis, Teradata utilities, UNIX, BO XI, Crystal reports

Location

APAC

Client Background

It is one of the largest banks in Singapore and Malaysia, with group assets of more than 224 billion SGD. Extensive networks of over 530 branches and representative offices in 15 countries and territories including Singapore, Malaysia, Indonesia, Vietnam, China, Hong Kong SAR, Brunei, Japan, Australia, UK and USA.

Business Challenges

  • The existing system lacked in providing
    • Single version of truth and allow making informed business Decision makings
    • BASEL II Compliance
    • Re Designing of complete Architecture
  • Heterogeneous Business Intelligence & Data Warehouse environment across different physical locations
  • Technology environment is not standardized

HCLT Solution

  • Customization of FS-LDM (Financial Services Logical Data Model) and implementation of  framework architecture
  • EDW Development and Implementation,EDW Process setup
  • Design and implementation of extracts for downstream applications - Data extracted from Teradata EDW using an ETL layer to supply to SCV (Single Customer View), GL reconciliation process and through downstream views to Fermat risk calculation engine
  • Architecture Re-designing (AMP* to B2DW) – AMP stands for Analytical Marketing Project
  • Historical Data processing (Change Management)

Benefits in business operations

  • Highly scalable solution to meet future growth requirements
  • Reusable ETL components (which comprises 60% - 80% of the cost and time of any data-driven initiative)
  • Meets Basel II requirements
  • Financial management solution to provide faster monthly closure
  • Structured and organized data within the warehouse, enabling accurate analysis of large volumes of data
  • Enhanced capability to answer business questions related to commercial banking, institutional investment activities, correspondent banking, and internal financial management
  • Integrated data with ‘single version of truth’
  • Provisioning of bundled products to customers and providing benefits across these products

business intelligence analytics

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