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Unified Data Warehouse Implementation Using Data Vault 2.0 for Enhanced Processing and Data Quality
  1. case
  2. Unified Data Warehouse Implementation Using Data Vault 2.0 for Enhanced Processing and Data Quality

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Unified Data Warehouse Implementation Using Data Vault 2.0 for Enhanced Processing and Data Quality

senlainc.com
Financial services
Banking & Finance

Challenges with Dispersed Data and Legacy Systems

Post-merger data fragmentation across three legacy systems caused delayed product launches, inconsistent reporting, data duplication, and escalating infrastructure costs. Outdated technology stacks hindered scalability and regulatory compliance, while poor data quality undermined decision-making and competitiveness.

About the Client

Major European bank operating across Europe, Asia, and Africa with 70,000+ employees, 15 million customers, and 20 subsidiaries

Objectives for Unified Data Warehouse Implementation

  • Establish a centralized 'golden source' of data
  • Improve data quality and consistency across subsidiaries
  • Reduce data processing time by 50%
  • Modernize technology stack to eliminate legacy system dependencies
  • Accelerate time-to-market for new financial products
  • Enable real-time regulatory reporting capabilities

Core System Functionalities

  • Data Vault 2.0 architecture for flexible schema evolution
  • Apache Airflow-managed ETL pipeline with Kafka data bus
  • Automated data quality validation and cleansing mechanisms
  • Integration with Greenplum MPP database for petabyte-scale processing
  • Microservices-based data ingestion from 20+ subsidiary systems

Technology Stack Requirements

Data Vault 2.0 methodology
Apache Airflow
Apache Kafka
Greenplum MPP database

System Integration Needs

  • Legacy banking databases (Oracle, SQL Server)
  • Regulatory reporting frameworks
  • Customer analytics platforms
  • Risk management systems

Performance and Scalability Expectations

  • Support 200% annual data volume growth
  • Ensure 99.99% data availability SLA
  • Maintain financial data encryption at rest/in transit
  • Achieve sub-second query response times for regulatory reports
  • Enable horizontal scaling across 100+ nodes

Expected Business Impact of Data Warehouse Implementation

Projected 200% improvement in data availability and reporting speed, 50% reduction in infrastructure costs, and 60% faster product launch cycles. The solution will unify 15 million customer records across 20 subsidiaries while ensuring compliance with financial regulations through standardized data governance.

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