Case Study: ARTC’s Insight Factory Managed Platform
Whilst ARTC has a rich history of successfully running a data program across its business, the organisation sought to evolve its approach and explore an alternative model for managing its significant and growing data requirements. As part of this initiative, ARTC looked to adopt a managed services model that would reduce internal overhead while maintaining enterprise-grade performance.
This led to the selection of the insightfactory.ai managed Lakehouse “The Insight Factory” a modern, production-grade environment built on Azure. The Insight Factory provides ARTC with a fully managed service, outsourcing the complexity of platform management while enabling continued acceleration of its data program. Importantly, the Lakehouse foundation is designed not only to strengthen governance and operational efficiency but also to unlock AI capabilities across the organisation.
insightfactory.ai was selected to deliver this transformation, leading ARTC’s full-scale migration from legacy systems into the managed Insight Factory, enabling the business to focus on value creation while insightfactory.ai ensures the platform remains evergreen, secure, and optimised.
“Partnering with insightfactory.ai has allowed us to modernise our entire data platform without the typical complexity or resource drain. Their Lakehouse deployment gave us a scalable, high-performance foundation, and the fully managed model means our internal teams can focus on driving value not running infrastructure.”
- Andrew Simpson, ARTC
The Problem
The Australian Rail Track Corporation (ARTC), a key national operator responsible for managing a vast freight rail network, was running an enormous volume of critical data workloads on their existing platform that had become increasingly complex to maintain. With a lean internal development team and a large workload to manage, the system demanded significant effort just to keep it running, leaving reduced capacity to focus on innovation or enable new capabilities.
At the same time, innovation in the data and AI ecosystem particularly from technology leaders (such as Databricks) was advancing at pace. ARTC recognised the need for a platform that could continuously evolve alongside this rapid innovation curve, providing a clear and simple pathway to production for workloads while making oversight and management of production operations more straightforward.
Importantly, ARTC had already established valuable intellectual property through the use of tools such as DBT and other components of its data stack. They wanted to ensure that this investment could be seamlessly carried forward into the new environment, without requiring an enormous reinvention effort or losing the benefits of prior work.
By seeking a managed platform model, ARTC aimed to free up its development team to focus on building and enabling new capabilities, rather than operating infrastructure. The goal was to ensure the organisation could keep pace with industry innovation, reduce operational overhead, preserve and leverage its existing IP, and unlock new opportunities for data and AI adoption across the business.
The Solution
insightfactory.ai was engaged to deploy the Insight Factory platform and lead ARTC’s migration to a fully managed Lakehouse within their existing Cloud tenant. The platform was rapidly deployed, providing an enterprise-grade foundation on which ARTC could modernise its data environment without disruption.
Working closely with ARTC, the team migrated all data, models, and workloads from the existing platform into the new Lakehouse environment. A critical element of this migration was ensuring that ARTC’s intellectual property, including DBT pipelines and other key assets, could continue to run and evolve within the managed platform. This approach preserved the value of prior investments while extending their impact and avoiding the need for costly reinvention.
By shifting to the insightfactory.ai managed services model, ARTC was able to transplant its existing IP into a modern, production-grade Lakehouse with minimal effort. The new environment freed up ARTC’s development team to focus on building new capabilities rather than maintaining infrastructure, while providing a simpler and more transparent way to oversee and manage production workloads. Most importantly, the platform established a secure and scalable foundation for the future, designed to unlock advanced analytics and AI use cases across the organisation.
The Value Delivered
The Insight Factory platform now underpins ARTC’s data and AI program, transforming how the organisation manages, governs, and scales its data. By migrating to a modern Lakehouse while preserving existing intellectual property, the solution provided both continuity and acceleration. ARTC’s mission-critical workloads now operate with production-grade stability, consistently achieving the highest levels of uptime. Performance has been significantly enhanced, with the platform delivering high-speed execution across both operational and analytical workloads and the scalability to keep pace with future innovation.
The shift also delivered greater resource efficiency, reducing the internal demands of platform management and allowing ARTC’s development team to redirect their focus towards building new capabilities. Crucially, prior investments such as DBT pipelines were seamlessly migrated and extended, ensuring that established intellectual property continued to generate value without reinvention. The Lakehouse architecture introduced a secure, governed, and cost-optimised design aligned with industry best practice, creating a resilient and future-ready foundation. With this platform in place, ARTC is positioned to rapidly enable advanced analytics and AI use cases, turning data into an engine for insight and innovation.
This engagement demonstrates how insightfactory.ai delivers mission-critical migrations at scale, providing not just a technology upgrade but a complete lifecycle transformation, one that preserves the strengths of the past while unlocking the possibilities of the future.
