Overview
Our client is a Fortune 10 organization operating within the nonprofit and education space that Nextant has supported for over eight years. Although part of a larger enterprise, this group operates as a global business organization serving a diverse customer base across multiple models, including managed and unmanaged accounts, IGO, SMB, Digital, and Enterprise segments.
The organization’s mission is to maximize reach and impact across nonprofit and education customers while driving meaningful consumption and adoption of its products and services. Each segment requires differentiated engagement strategies, operating models, and success metrics, creating a highly complex operational and analytical environment.
As the organization scaled globally, leadership increasingly depended on analytics to support strategic planning, operational execution, and performance measurement across regions, segments, and offerings.
The Challenge: Scaling Analytics in a Complex Data Landscape
Nextant was engaged to support executive and operational reporting, insights generation, data engineering, and the structuring of analytical data assets.
The core challenge was aligning growing business demands with a fragmented data ecosystem composed of multiple upstream sources with varying data quality, structure, and ownership. Over three major engagements, the organization experienced nearly double growth, significantly increasing data volume and complexity.
While Power BI initially met reporting needs, limitations emerged around dataset scalability, transformation complexity, refresh reliability, and capacity management. Combined with fragmented upstream systems, these constraints made it difficult to deliver consistent, trusted, and governed insights at enterprise scale.
To support continued growth and reliable decision-making, the organization required a more robust, end-to-end analytics platform, driving the transition to Microsoft Fabric.
The Solution: A Microsoft Fabric–Centered Architecture
Nextant’s approach focused on aligning business objectives with data and analytics capabilities. Given the diversity of data sources, the first priority was validating the data landscape to ensure it accurately reflected the business.
This effort included identifying data gaps, correcting errors, resolving inconsistencies, and flagging missing or incomplete information. Establishing a trusted data foundation was essential before expanding analytics capabilities.
Once this foundation was in place, Nextant re-architected the analytics ecosystem, transitioning from a Power BI–centric model to a Microsoft Fabric–centered architecture. This unified platform integrated data ingestion, transformation, modeling, governance, and reporting, enabling scalable and consistent analytics while preparing the organization for future growth.
Technology and Delivery Approach
The Microsoft Fabric implementation leveraged a centralized Fabric Lakehouse as the foundation for scalable data storage and transformation. Fabric Pipelines and Dataflows ingested data from client-hosted SQL Server systems and Analysis Services cubes using optimized DAX queries.
A Medallion Architecture was implemented with a focus on Silver and Gold layers. Curated data was ingested into the Silver layer, where SQL-based transformations produced structured tables. Gold-layer datasets were optimized for Power BI consumption, ensuring consistent metrics and improved performance.
Power BI reports were rebuilt to consume Fabric-based semantic models, standardizing business logic and enhancing reliability. Supporting tools such as DAX Studio were used to optimize query performance.
Delivery followed an agile, phased approach designed to maintain business continuity while modernizing the platform. Governance and security were implemented at the platform level, shifting access control from individual reports to Microsoft Fabric.
Collaboration and Execution
The engagement relied on a clearly defined collaboration model. Data and Solution Architects designed the Fabric architecture and governance framework, Report Developers migrated and aligned Power BI reports, and Project Management ensured alignment between business priorities and technical execution.
While the primary client stakeholder brought deep business expertise, technical ownership of the data platform was initially limited. A secondary stakeholder with strong Microsoft Fabric expertise became a key partner, while the Project Manager played a critical role in bridging business and technical teams.
The transition followed a phased roadmap: architecture and foundation setup, data modeling and reporting migration, and ongoing governance, optimization, and monitoring.
Results and Business Impact
The move to Microsoft Fabric delivered measurable improvements across data quality, performance, governance, and scalability. The organization gained a single, trusted view of the business through centralized data transformations and standardized metrics.
Automated and reliable data refreshes reduced operational overhead, while faster report performance improved user experience and adoption. Platform-based governance strengthened security and compliance, and increased data capacity positioned the organization to support continued growth.
Overall, the analytics environment evolved from a report-centric setup into a scalable, governed, and future-ready enterprise data platform.
Conclusion
By implementing Microsoft Fabric, Nextant enabled the organization to overcome scalability and governance limitations while establishing a trusted, unified analytics foundation. The new platform supports confident decision-making, operational efficiency, and long-term growth, ensuring continued impact across nonprofit and education segments.
Frequently Asked Questions
What is Microsoft Fabric, and why is it important for enterprise analytics?
Microsoft Fabric is an end-to-end analytics platform that unifies data, governance, and reporting, enabling scalable and consistent enterprise analytics.
When should an organization move beyond a Power BI–centric architecture?
When data volume, transformation complexity, refresh issues, or governance limitations prevent analytics from scaling effectively.
How does Microsoft Fabric improve scalability and performance?
By centralizing data processing in a Lakehouse architecture and reducing complexity at the reporting layer.
How does Microsoft Fabric support data governance and security?
Through centralized access control, standardized data models, and platform-level security instead of report-level management.
Can existing Power BI reports be migrated to Microsoft Fabric?
Yes. Reports can be rebuilt to use Fabric datasets while improving performance and consistency.
