About

A leading secure logistics and technology services organisation operates across Australia, New Zealand, and Southeast Asia, providing critical support for financial institutions, retailers, and government agencies. With decades of experience in the secure transport and management of currency and valuable assets, the organisation has evolved into a technology-driven provider of end-to-end cash management, digital payments, and asset protection solutions.

Challenge

As part of a broader digital transformation initiative, the organisation’s Data and Analytics (D&A) team sought to build a scalable Enterprise Data Model (EDM) to centralise, structure, and govern data across multiple systems and business domains.

The primary goals were to:

  • Create a single source of truth for HR, Fleet Management, System Health, Customer, and Finance reporting.

  • Integrate disparate data sources, including legacy systems and spreadsheets, into a modern cloud-based data platform.

  • Establish a foundation for analytics consistency and governance across all departments.

  • Enable self-service analytics through semantic data models and secure visual reporting.

The enterprise technology stack included Snowflake (data warehouse), Talend (ETL/ELT), and Power BI (semantic modelling and reporting).

Solution

Enterprise Data Model Design

AGER BI began by designing the EDM using SQL Database Modeler (SQL DBM) to define relationships, business rules, and table structures. This blueprint became the foundation for scalable data integration and governance.

Data Integration and Transformation

Data from multiple operational systems was staged in a Snowflake landing zone, where AGER BI developed Talend ELT pipelines to transform, cleanse, and load data into dimension and fact tables. The architecture leveraged Type 2 Slowly Changing Dimensions (SCD2) and UPSERT operations for efficient, incremental updates and historical traceability.

Semantic Modelling and Analytics Enablement

Once the EDM was established, Power BI semantic models were created for each business area, Human Resources, Fleet Management, System Health Indicators, Customer Insights, and Financial Operations. These models provided consistent KPI definitions, optimised performance, and reusable datasets across business units.

Collaboration and Knowledge Transfer

AGER BI embedded directly with the D&A team to provide ongoing mentoring, code reviews, and optimisation support, ensuring internal capability uplift and sustainable ownership of the data platform.

Benefits

The project delivered a unified, cloud-based enterprise data environment that transformed the way the organisation captures, manages, and uses data across critical business functions.

Key outcomes included:

  • Data Accuracy & Trust: A centralised, governed EDM ensures consistent and reliable insights across departments.

  • Operational Efficiency: Automated ELT processes and scheduled data refreshes provide up-to-date visibility without manual intervention.

  • Improved Performance Monitoring:

    • Human Resources: Headcount, turnover, retention, leave, absenteeism, and diversity.

    • Fleet Management: Vehicle costs, repairs, maintenance, and asset utilisation.

    • Customer Operations: Cash collected and supplied, service quality metrics, and missed service trends.

    • System Health Indicators: Data quality, record counts, and load validation between landing and EDM layers.

    • Funds Ledger: Cash on hand, aged balances, and branch-level summaries.

  • Stronger Governance: Data lineage, version control, and ownership frameworks embedded in Snowflake and Talend.

  • Scalability: The architecture now supports future analytics use cases, including forecasting, predictive maintenance, and automation.

Through a well-designed data strategy and cloud-based data architecture, the organisation now benefits from greater insight, reliability, and strategic agility, enabling confident, data-driven decision-making across every level of the business.