Answering questions across applications
"In recent years, there has been an increasing need to answer questions based on data from different applications," explains Edwin. "Traditional BI systems are less suitable for such questions, because they generally provide data collections per system. At Prescan, we need cross-domain data collections, where we can, for example, combine data from the Mendix ERP system with financial data from Exact Online. For this combination, we called in the help of AMIS."
Jorrit Nijssen, data architect at AMIS Conclusion: "Traditional BI solutions make it difficult to combine data from different applications. Each Mendix application has its own data model and field definitions. By including data sources in a single semantic model, the data definition becomes unambiguous and comparable, regardless of the source system. We paid attention to the semantic model so that new sources can be added without much impact."
Jorrit continues: "Unlocking data directly in Power BI increases complexity and unreliability if the data comes from different sources. For a company like Prescan with a compact IT department, a SaaS solution for data products such as dashboards and reports, among others, is preferable to a PaaS solution. Microsoft Fabric offers Prescan the ease of use of Power BI supplemented with professional data processing."
Microsoft Fabric as the foundation for intelligent data platform
Prescan chose Microsoft Fabric for their data platform to collect, combine, and analyze large amounts of data from a variety of sources. AMIS played a crucial role in unlocking source systems such as Exact-online and Mendix applications. In addition, AMIS designed and implemented the semantic model and set up metadata-driven data flows. This resulted in a Medallion architecture with a Data Lakehouse in which data is enriched step by step until it is reliable and usable for the business.
End-to-end data-analyseplatform
Microsoft Fabric is an analytics platform that provides a single, integrated environment for data processing and collaboration on data projects. With Microsoft Fabric, you can ingest, store, process, and analyze data in a single environment. It is an integrated SaaS solution, ready to use. so you can use it without spending time configuring standalone Azure services like Azure Data lake, Azure Data Factory, or Azure Synapse. This makes it ideal for companies like Prescan with an already largely cloud-based infrastructure.
Insight into current status and possibility to look ahead
Prescan needed to quickly develop a solution that is stable and scalable. It also had to be adaptable and expandable. Edwin: "Because we were already using Microsoft Azure, choosing Microsoft Fabric was a logical step. It fits well with the size and complexity of our organization and offers opportunities to quickly meet our needs."
In the project, AMIS unlocked both Mendix and Exact-Online data sources over a period of 16 weeks and translated them into data products via pipelines. As a result, Prescan now has extensive controls for business operations. Edwin: "The reports and insights enable us to better manage our organization and gain detailed insight into our activities, planning, individual performance, staffing and data-driven decisions. This data forms the basis for a number of KPIs aimed at improving the governance of our organization and quality of care.
Solid and future-proof solution
AMIS was chosen for this assignment because of their professional approach, experience and pragmatism. Edwin: "It is nice to work with a party that asks the right questions, thinks about the long term and challenges us, which prevents shortcuts." The chosen solution has a layered structure in which reports are disconnected from the sources via an intermediate layer. This ensures that changes and expansions can easily be implemented in the future without impacting the reports. Edwin: "AMIS has created a robust, future-proof architecture that makes the system scalable. Their data engineering expertise is evident from thinking this through in advance. As a result, we can now easily connect new sources and add pipelines."
