Municipality Accelerates Data-Driven Work with Microsoft Fabric

The Work & Income Department of a large Dutch municipality helps thousands of residents receiving welfare benefits find employment each year. To connect employers and job seekers, the municipality uses a matching application.

This application is a valuable tool, but without clear and reliable data, it was difficult to properly assess the results and make targeted adjustments. The municipality wanted to gain more control over its results while simultaneously taking the next step toward AI-driven operations.

To achieve this, one thing was essential: a robust and scalable data platform.

The challenge: fragmented data and limited insights

The Work & Income department wanted to gain more insight into the job seeker database and be able to steer toward results more quickly and reliably. However, the necessary data was scattered across multiple sources. Generating reports was a laborious process, and the quality of the figures was difficult to verify.

A BI Business Consultant at the municipality explains:

“We needed dashboards that we could understand and trust ourselves. No more black boxes.”

Within the organization, there was also a growing need to work with AI, for example, to develop code more quickly. This requires a solid and easily accessible database.

The municipality had already been cautiously experimenting with Microsoft Fabric but was looking for an experienced partner to quickly move from an initial exploration to a working and future-proof foundation.

The approach: Fabric60—from vision to foundation in 60 days

The municipality chose Macaw and launched Fabric60. This approach establishes a solid foundation in 60 days upon which the organization can continue to build. No lengthy analysis phase—just a concrete and results-oriented process.

The process began with a joint workshop with the broad project group focused on the matching application. Together, we identified the objectives, challenges, and priorities. Product Owners, data experts, and other stakeholders were involved from the very beginning.

Based on these insights, our specialists developed a data platform architecture in Microsoft Fabric. At the same time, Microsoft Purview was implemented to effectively ensure data governance and data lineage.

The municipality took on the development of the reports largely on its own. This fostered an equal partnership in which both organizations contributed their own expertise and took joint responsibility for the outcome.

Technical limitations were also not allowed to slow down progress. When a system limitation stood in the way of an immediate launch, the teams worked together to find an alternative solution. This allowed the project to continue quickly and pragmatically.

Even experienced technical specialists within the municipality became enthusiastic about the possibilities of Microsoft Fabric during the project. The collaboration was characterized by short lines of communication, speed, and a practical approach.

The result: scalable, reliable, and ready for an AI-driven future

The municipality now has a single powerful and scalable data platform that consolidates data from various sources. As a result, it is no longer necessary to constantly switch between different tools and providers.

Microsoft Fabric brings together the capabilities for collecting, processing, analyzing, and presenting data within a single environment. Reports are reliable, up-to-date, and immediately usable for decision-making at both the team and individual levels.

The most significant benefit is the foundation that has now been established. The municipality has greater control over its data and can continue to work on reports, analyses, and future AI applications from a consistent and scalable environment.

Collaboration with Impact: Pragmatic, Goal-Oriented, and Human-Centered

The municipality looks back positively on its collaboration with Macaw. In addition to the technical implementation, our specialists helped the organization develop a roadmap for the further implementation of Microsoft Fabric.

Macaw shared best practices, assisted in designing a robust infrastructure, and guided the integration of the platform into the existing environment.

With these insights, the municipality can develop a long-term strategic plan. It can also further improve the efficiency of data flows and pipelines.

The collaboration was characterized by short lines of communication, a practical approach, and a shared focus on concrete results.

The Next Step: From Reporting to Predicting

In the coming period, the municipality aims to build further on the foundation that is now in place. By analyzing historical data, it hopes to better predict which job seekers need what kind of support.

This will allow the department to tailor its services more precisely and guide residents more effectively toward employment. Data will thus be used not only to look back and report, but also to identify patterns and better predict future needs.

The foundation in Microsoft Fabric makes it possible to shape this development in a controlled and step-by-step manner. In this way, the municipality is working toward a situation in which data increasingly supports decision-making and the improvement of services.