Case study

AMSA Partners with Altis Consulting to Fast-Track Their Data Platform Implementation with Altida™

5 minute read

25 March 2025

Data sources connected

1000+

Objects created in data warehouses

Minutes to stage a new table from a source

metadata driven solutions: Alitda

The Australian Maritime Safety Authority (AMSA) is the national agency responsible for ensuring safe navigation, protecting the marine environment, and providing search and rescue services in Australian waters. Established in 1990, AMSA regulates vessel safety standards, enforces international maritime conventions, and oversees pollution prevention measures. It manages Australia’s emergency response to maritime incidents, including coordinating search and rescue operations for vessels, aircraft, and people in distress.

The vision

Altis was engaged by the Australian Maritime Safety Authority (AMSA) to design and deliver a modern cloud-based reporting and analytics environment (RAE).

The RAE was envisaged to provide a centralised single source of truth for reporting and analytics, drawing data from AMSA’s diverse operational systems’ data holdings. Within the RAE, data from sources would be standardised, integrated, and transformed to support a suite of data products. These data products would then be able to be shared across business areas, driving better-informed risk-based decision making and more efficient operations. The RAE would additionally be capable of reliably surfacing data into business intelligence and advanced analytics tools for reporting and data science.

The solution

Altis proposed a simple and low-cost architecture in Microsoft Azure which could be expanded with more advanced services as AMSA’s data engineering and analytics capability grew. As part of this project Altis was also engaged to deploy the Altida framework. Altida is our proprietary data ingestion framework which significantly streamlines data engineering tasks by utilising a metadata-driven process to manage ETL tasks.

Prior to Altis commencement, AMSA had undertaken work to set up their Azure Landing Zone architecture with the RAE being the first project on the platform. In the early stages of the project Altis further validated the data platform architecture based on AMSA’s requirements, adjusting the details of the original architecture as required. Altis then worked collaboratively with AMSA’s internal IT team to set up RAE services and infrastructure in Azure and configure the security and access model according to the design. Additionally, Altis advised and provided support on any additional security hardening required to support handling of sensitive data.

In parallel, Altis worked in collaboration with AMSA data engineers to establish an initial RAE prototype environment to prove the Altida framework against use cases utilising non-sensitive data. Upon platform sign off by AMSA IT, the Altida prototype was integrated into the platform, with AMSA data engineers ready to implement further use cases.

The outcome

A new data platform featuring Altida was successfully implemented at AMSA.

"The metadata-driven ETL processes were easy for our team to learn and implement, requiring minimal training and no specialised skills. Altis Consulting’s support has been invaluable in transforming our data environment."

This enabled AMSA’s data engineers to become productive almost immediately, resulting in rapid delivery of initial data products to the business.

Following successful RAE implementation in lower environments, Altis worked with AMSA to implement secure connections from the RAE to reporting and analytics tools such as Power BI. Altis continues to provide data architecture and data engineering support to the AMSA data team as they continue to expand the RAE with new datasets and reports.

Thanks to the new platform AMSA has been able to securely centralise their data holdings. This has enabled AMSA to:

Create a single source of truth for enterprise reporting and analytics
Reduced build time and effort for new data products, giving business areas insights faster
Ability to rapidly integrate diverse datasets from multiple source systems
Implement improved data validation techniques
Use new analytics capabilities to support use cases such as risk modelling

The solution architecture

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