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Australian Public Sector Entity Modernized Legacy Systems and Enabled Real-Time Analytics Through Azure Data Platform

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Overview

The client is a large public sector entity in Australia that manages transactional, analytical, and historical data across multiple systems. The client sought to enhance scalability, performance, and security while improving user experience and enabling real-time analytics.

Challenges

The existing IT landscape was fragmented, with transactional and analytical data stored in on-premise Oracle databases and Oracle Forms. The system faced multiple issues:

  • Scalability and performance bottlenecks.
  • Security and user experience limitations.
  • Lack of real-time analytics and modern data integration capabilities.
  • Increasing maintenance complexity due to legacy infrastructure.

Solution

Coforge implemented a Pega-driven Business Process Management (BPM) and Azure-based Data Lake and Warehouse solution using Azure PaaS components to modernize VG NSW’s legacy environment:

  • Built a cloud-native data platform leveraging Azure Data Factory, ADLS Gen2, Azure SQL, Event Hub, and Power BI.
  • Used Pega for workflow automation, transaction management, and historical data access through DWH integration.
  • Deployed two Azure SQL databases for handling transactional and analytical workloads.
  • Implemented Azure Event Hub to process real-time data from Pega and visualize it in Power BI.
  • Executed data migration from on-premise Oracle to Azure SQL using Azure Data Factory.
  • Established data quality checks and validations to ensure integrity, accuracy, and reliability.
  • Introduced proactive remediation for data issues inherited from legacy systems.

The Impact

  • Delivered a scalable and secure Azure-based data platform for both real-time and batch analytics.
  • Enabled 360° client view through integrated Pega and Azure systems.
  • Enhanced data integrity, governance, and security via Azure AD and segregation of duties.
  • Improved productivity and operational efficiency through automation and self-service BI.
  • Reduced technical debt by migrating legacy data systems to a future-ready cloud ecosystem.

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