How do you modernize a data platform without starting over? This customer story shows how SPS Corporation, a Melbourne-based group of businesses, responded when massive data volumes slowed its Dynamics 365 data extraction. With Timextender, it moved from on-premises SQL Server to Microsoft Fabric and Power BI Premium by adapting its existing solution instead of rebuilding it. Read the story to learn how SPS Corporation modernized cost-effectively while protecting years of business logic and reporting.
Why did SPS Corporation move from BYOD to Microsoft Fabric?
SPS Corporation had been a long-term Microsoft customer, running AX 2012 with an on-premises SQL data warehouse built using Timextender. When they migrated to Dynamics 365 Finance Operations (D365FO), they followed Microsoft’s then-recommended “bring your own database” (BYOD) pattern for data extraction.
Over time, this approach became a bottleneck:
- Massive data volumes across multiple business units (property, recreational vehicles, art and picture framing) made BYOD increasingly non-performant.
- The business needed a modern, scalable data platform that could keep up with growth without sacrificing performance.
- They wanted to avoid a complete reimplementation of their analytics solution and protect the investment in existing business logic and reporting.
As Microsoft’s own data platform evolved—first with Azure Synapse Link for Dataverse, then with Microsoft Fabric (OneLake and Lakehouse)—SPS saw an opportunity to:
- Move from on-premises SQL Server to Microsoft Fabric.
- Adopt Fabric Lakehouse and Power BI Premium for analytics.
- Use Timextender to adapt their existing solution instead of rebuilding it.
In short, the shift to Microsoft Fabric was driven by the need to handle growing data volumes, improve performance and scalability, and future-proof their analytics platform—while avoiding the cost and risk of starting over.
How did Timextender help SPS migrate without starting over?
Timextender played a central role in allowing SPS Corporation to migrate in stages—first from AX 2012 to D365FO, then from on-premises SQL Server to Microsoft Fabric—without starting from scratch.
Key enablers were:
1. Unified Metadata Framework for “lift-and-shift”
- Timextender’s Unified Metadata Framework meant the initial move from AX 2012 to D365FO was essentially a lift-and-shift.
- Data from both AX 2012 and D365FO was seamlessly integrated in the same data warehouse.
- Business users could perform long-term trend analysis without noticing where AX 2012 data ended and D365FO data began.
2. Alignment with Microsoft’s Medallion Architecture
- Timextender has long been designed in line with what Microsoft calls the Medallion Architecture.
- When Microsoft introduced Azure Synapse Link for Dataverse and then Fabric Lakehouse, SPS could adapt rather than rebuild.
- Timextender simply switched from generating SQL stored procedures to generating Python notebooks for Fabric Lakehouse.
3. Configuration changes instead of reimplementation
- Each platform shift—AX 2012 to D365FO, SQL Server to Fabric—became a configuration change inside Timextender.
- The existing business logic, data models, and reporting were preserved.
- This approach made the migration to Microsoft Fabric cost-effective, as highlighted by SPS’s CFO.
As a result, SPS modernised its data platform step by step, reusing the same metadata-driven foundation instead of rebuilding pipelines and models for every new Microsoft technology.
How is SPS preparing for AI-ready analytics with Timextender and Fabric?
SPS Corporation is using Timextender and Microsoft Fabric not just to modernise reporting, but also to prepare for AI-ready analytics in a governed way.
1. AI-ready data foundation
- Timextender unifies and automates the entire data lifecycle—from integration and transformation to quality assurance and orchestration.
- This creates trusted, reusable data products that can be deployed to platforms like Microsoft Fabric without locking business logic to a single vendor.
- The result is a data estate that is structured and governed enough to support AI scenarios.
2. MCP Server for governed AI and semantic models
- With Timextender MCP Server, SPS is positioning itself for governed adoption of non-hallucinating AI analytics.
- MCP Server can connect to semantic models, allowing SPS to guide tools such as XPilot Analytics and Claude with additional natural language descriptions and explanations of their data.
- This helps AI systems interpret data more accurately and consistently with business definitions.
3. Future-proof, analytics-ready architecture
- Running on Microsoft Fabric with Power BI Premium, SPS has a platform that can evolve with Microsoft’s roadmap.
- Timextender’s metadata-driven approach means future changes in the Microsoft ecosystem can be handled as adaptations rather than full rebuilds.
For SPS, this combination of Fabric, Power BI Premium, and Timextender provides a practical path to reimagine analytics with AI—grounded in governed, high-quality data rather than experimental or ad hoc approaches.