grenke: A Scalable Foundation for Analytics and AI
Business-Critical Data Warehouse Migration to Microsoft Fabric in a Highly Regulated Financial Environment in Five Months
Data Warehouse Migration to Microsoft Fabric at grenke
In just five months, grenke and b.telligent migrated a complex, business-critical on-premises data platform to Microsoft Fabric. grenke now has a secure, future-ready foundation for reporting, analytics, and upcoming AI and machine learning use cases.
Quick Facts About the Project
4.5
4.5 TB of data from 19 source systems migrated to Microsoft Fabric in just five months.
Initial Situation & Challenge
grenke, a global specialist in small-ticket leasing, operates in a highly regulated financial environment where data availability, security, and traceability are core requirements. This is exactly where its existing data warehouse, DWH3, had reached its limits.
Over the years, the on-premises architecture based on SQL Server, SSAS, and Power BI Report Server had grown to 4.5 TB of data, around 1 TB of which was in daily circulation. It was fed by 19 source systems with roughly 3,000 tables and views. Any further expansion would have added complexity without making the platform more future-ready. With the strong growth grenke is targeting in the coming years, the existing solution would not have been able to keep up.
grenke therefore decided to move to Microsoft Fabric. The goal: a modern, centrally governed analytics platform with clear governance structures that would take over existing reporting seamlessly and lay the foundation for future data and AI use cases. The timeline was tight: five months for a business-critical migration. That called for clear priorities and closely aligned architecture work from day one.
Solution
Assessment, Blueprint, and Proof of Concept
The project started with a thorough assessment. The interdisciplinary b.telligent team analyzed data models, ETL and ELT pipelines, and dependencies within the existing DWH3. The result was a migration blueprint for Microsoft Fabric, aligned with grenke. The target architecture combines OneLake, Lakehouse, Warehouse, and semantic models with clear guidelines for workspaces, capacities, security, roles, access, and data governance.
Before the rollout went broad, a proof of concept validated the critical architecture decisions and the planned migration path. This made it possible to identify technical risks early and reduce them in a targeted way.
Controlled Data Transfer to the Cloud
A particular challenge was moving the entire data volume reliably from the on-premises landscape to the cloud. With 4.5 TB of data, numerous dependencies, and a tight schedule, the transfer had to be managed so that data completeness and consistency remained traceable at all times. The team therefore split the transfer into controlled steps, backed by technical checks and data reconciliations, creating a solid basis for building the Fabric data pipelines.
Rebuilding the Data Pipelines on Microsoft Fabric
On this verified foundation, the team rebuilt data flows, transformation logic, and operational processes using Fabric Data Factory, notebooks, Lakehouse storage, and the warehouse layer, and integrated the existing dbt Cloud configuration. Technical tests, data reconciliations, and defined error-handling processes ensured that no functionality and no data quality were lost along the way.
In parallel, the team established the governance and operational foundations: workspace design, access models, monitoring, and documentation, closely coordinated across project management, DWH architecture, Fabric architecture, and data engineering. Combining legacy know-how with Fabric expertise was key to handling the large number of sources and data objects within the ambitious timeline.
Microsoft as an Accelerator
Microsoft supported the project through ECIF as part of the Azure Frontier Offer. The funding helped to further safeguard the architecture, proof of concept, and migration. grenke and b.telligent were jointly responsible for design, implementation, and operational enablement.
Go-Live, Knowledge Transfer, and Hypercare
Finally, b.telligent supported the go-live, knowledge transfer, and hypercare phase, keeping operations stable well beyond the cutover.
Voices From the Project
With b.telligent, we migrated a complex DWH environment to Microsoft Fabric within an ambitious timeframe. The team combined rigorous architecture work with pragmatic implementation, made risks transparent early on, and worked with us to develop robust solutions. As a result, grenke has a scalable foundation for analytics and AI.
Thomas Kronawitter
Head of Data-Driven Applications & Services at grenke
For a migration of this scale, success depends not only on architecture and engineering but also on effective collaboration between the client, consulting team, and technology partner. Together with grenke and Microsoft, we quickly established the foundations for safely replacing DWH3 and building the data platform’s long-term future on Microsoft Fabric.
Matthias Nohl
Account Manager for grenke and Management Consultant at b.telligent
b.telligent Services at a Glance
DWH3 Analysis & Migration Blueprint
Assessment of data models, ETL and ELT pipelines, dependencies, and operational requirements.
Fabric Target Architecture
Design of OneLake, Lakehouse, Warehouse, semantic layer, workspaces, and capacity model.
Proof of Concept
Validation of critical architecture decisions, the migration approach, and technical feasibility.
Data Migration & Engineering
Rebuild of data pipelines and transformation logic with Fabric Data Factory, notebooks, and dbt Cloud.
Security, Governance & Operations
Role and access concepts, architecture reviews, monitoring readiness, and error handling.
Go-Live & Hypercare
Data reconciliations, technical testing, documentation, knowledge transfer, and support for the transition into operations.
Results & Successes
Highlights
Complex Migration in Five Months
4.5 TB of data, around 1 TB of daily data volume, 19 source systems, and roughly 3,000 tables and views successfully moved to Microsoft Fabric.
Fabric Target Architecture with Built-In Governance
OneLake, Lakehouse, Warehouse, semantic models, and Power BI form a scalable platform with integrated security, role, and governance structures.
Smooth Transition into Operations
Standardized tests, data reconciliations, a documented target architecture, knowledge transfer, and hypercare ensure stable operations and the continued development of the platform.
Five months after kickoff, the entire DWH3 landscape was running on Microsoft Fabric, including all source systems, tables, and views that had accumulated over the years. The new environment replaces key parts of the legacy on-premises architecture with a scalable SaaS platform featuring integrated security and governance capabilities. Standardized tests, data reconciliations, and clearly defined error-handling processes ensure that the migrated data pipelines run reliably in production.
grenke is now less dependent on legacy infrastructure and has a unified technology foundation for reporting, analytics, and future AI and machine learning scenarios. The documented target architecture, clear role models, and structured knowledge transfer make it easier to operate the platform sustainably and keep developing it.
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