Selected engagements across enterprise data and information change.

Challenge

Concurrent ERP and care-management replacements meant resident, clinical, and funding data had to be reconciled and trusted across systems under operational and compliance pressure, while reporting was fragmented across disconnected platforms.

Key capabilities involved

• Data Quality & Controls
• Data Integration
• BI & Advanced Analytics
• Cloud Data Platforms
• Data Governance
• AI, ML & Data Science

What DataVirtue contributed

• Provided transformation advisory across the ERP, care, and analytics workstreams.
• Led data migration for ERP and care-management systems, underpinned by deep data-quality analysis and complex transformations across resident, clinical, and funding data.
• Implemented a cloud analytics platform integrating ERP, care, workforce, and operational systems on a governed lakehouse architecture.
• Established automated data-quality and governance controls, and applied generative and agentic AI techniques to automate previously manual data-engineering tasks.

Challenge

Business change across investment, insurance, and superannuation entities was constrained by outdated systems, limited governance, and data foundations not ready for advanced analytics or AI.

Key capabilities involved

• Data Strategy
• Enterprise Data Architecture
• Data Office
• Cloud Data Platforms
• Data Governance
• AI Readiness & Responsible AI
• Data Modelling

What DataVirtue contributed

• Developed a future-focused enterprise data strategy and modern data architecture across all data initiatives.
• Led cloud migration of the enterprise data warehouse to Azure and helped establish a central Data Office.
• Developed an enterprise-wide data model and a data shopfront for consumption, with Microsoft cloud-readiness assessments and an AI roadmap.
• Defined data policies aligned to DAMA and TOGAF and to ISO 27001-informed security controls, and enabled Data Stewards through classification workflows that improved data quality.
• Supported secure, agile delivery through a DevSecOps approach.

Challenge

Reporting was fragmented and tightly coupled to outdated SAP data structures, making agency-wide reporting across finance, HR, performance, and investment domains slow and inconsistent — and it needed to align with QGCIO, QGEA, and IIRF standards.

Key capabilities involved

• BI & Advanced Analytics
• Enterprise Data Architecture
• Data Modelling
• Enterprise Reporting
• Self-service analytics
• Spatial analytics

What DataVirtue contributed

• Led the architecture integrating SAP FI/CO/AP/AR/AM with corporate systems such as HRIS and performance platforms.
• Designed modern data models (Data Vault and Kimball) that cleanly separated reporting from SAP's legacy schema.
• Enabled advanced visualisation, spatial reporting, and executive dashboards (Power BI, Tableau, ESRI ArcGIS).
• Delivered cloud and big-data architecture prototypes using R and Python tooling to position agencies for future analytics.

Challenge

Inconsistent definitions and integration approaches across systems limited data trust and reuse, with governance practices needing a contemporary refresh.

Key capabilities involved

• Enterprise Data Architecture
• Information Policy & Standards
• Data Quality & Controls
• Data Integration
• Data Governance

What DataVirtue contributed

• Delivered an Enterprise Conceptual Data Model giving a shared, business-aligned view of core data domains.
• Developed and refreshed a Data and Information Policy and Standards Register aligned to organisational objectives.
• Defined Data Integration and Engineering Patterns to standardise ingestion, transformation, and sharing.
• Delivered Enterprise Data Quality and Data Integration Frameworks embedding repeatable controls and responsibilities.

Challenge

Legacy systems and limited cross-jurisdictional data sharing held back modernisation, with complex requirements around security, sensitivity, and inter-jurisdictional exchange.

Key capabilities involved

• Information Architecture
• Taxonomy & Classification
• Master Data
• Information Sharing
• Enterprise Data Architecture
• Cloud Data Platforms

What DataVirtue contributed

• Led information architecture end-to-end: current-state assessment, target-state design, and enterprise data models, taxonomies, and classification standards.
• Architected strategic platforms for master data management, data engineering, information sharing, and analytics, addressing security and sensitivity requirements.

Challenge

Legacy eDRMS and correspondence platforms, inconsistent classification, and information-management policies needing a contemporary uplift made content hard to manage, secure, and retrieve.

Key capabilities involved

• Information Management
• Records & Content Architecture
• Taxonomy & Ontology
• AI & Automation Strategy
• Information Security
• Data Governance

What DataVirtue contributed

• Reviewed and uplifted Enterprise Information Management policies and standards, and produced an EIM Policy Map.
• Designed the Enterprise Content Management architecture and roadmap to replace legacy eDRMS and correspondence platforms.
• Developed a conceptual taxonomy and ontology model for consistent content classification and retrieval.
• Delivered an AI and automation strategy for the ECM transformation using a human-centred design approach, with advisory across the information security framework, requirements, and supporting data migration strategy.