Success Story BÄKO HANSA BÄKO HANSA moved its Qlik backend to the cloud, streamlined data integration, and standardized KPI management with iVIEW Dataflow and iVIEW Library.
Success Story Keller Unternehmensberatung AG Keller Unternehmensberatung modernized its HEBES benchmarking platform using Microsoft Fabric and Power BI, enabling faster analyses, secure data processing, and flexible self-service analytics.
Success Story BÄKO HANSA BÄKO HANSA moved its Qlik backend to the cloud, streamlined data integration, and standardized KPI management with iVIEW Dataflow and iVIEW Library.
Success Story Keller Unternehmensberatung AG Keller Unternehmensberatung modernized its HEBES benchmarking platform using Microsoft Fabric and Power BI, enabling faster analyses, secure data processing, and flexible self-service analytics.
Databricks Migration in Logistics From Azure SQL Server to a Scalable Data PlatformA global transport and logistics provider migrated its data platform for the Air & Sea division from Azure SQL Server to Azure Databricks. The results: data refreshed three times a day instead of once, a 90% reduction in security data volume, and a stable platform supporting thousands of Power BI users.Challenges Solution Results FAQ At a glance IndustryTransport & Logistics (International) DivisionAir & Sea, Data Platform Department PlatformAzure Databricks, Delta Lake, Power BI Results3× more frequent data refreshes, 90% less security data Initial Situation The client is a global transport and logistics company whose Air & Sea division relies on data for day-to-day operations and informed business decisions. Thousands of employees across the organisation use Power BI reports to monitor and analyse shipments, operational performance metrics and commercial KPIs.The existing data platform was built on Azure SQL Server. All data transformations were executed through stored procedures and orchestrated using Azure Data Factory. The processed data was then loaded into semantic models in Azure Analysis Services, which served as the foundation for the Power BI reports.The architecture had evolved organically over several years, becoming increasingly complex and difficult to maintain. At the same time, the existing platform could no longer adequately meet the division's growing demands for data freshness, reliability and availability. The challenges Long processing times: Only one data load per day was possible, meaning data was often up to 24 hours old. Redundant logic: Duplicate implementations of data transformations increased processing times and the risk of inconsistent results. Hidden business rules: Critical business rules were embedded in lengthy SQL stored procedures, making them difficult to understand and trace. Slow semantic models and inefficient row-level security: Extremely large security tables significantly slowed down report performance. Limited scalability as data volumes and user numbers continued to grow. The Solution: Migrating from Azure SQL Server to Azure Databricks Migration with Added ValueRather than translating the stored procedures line by line, we analysed each procedure, identified the underlying business rules and restructured the pipelines in Databricks. Redundancies were eliminated and recurring transformations consolidated. The result is a leaner, faster data processing layer built on Delta Lake, along with a documented overview of the client's business rules.Seamless Integration into the Existing Azure EcosystemThe new Databricks pipelines are orchestrated using Azure Data Factory and Azure Synapse Pipelines. This allows the solution to integrate seamlessly into the existing operational environment without requiring additional tools.Optimised Semantic ModelsWe conducted a comprehensive review of the Azure Analysis Services models and optimised their design. This reduced refresh times and improved report responsiveness in Power BI.Redesigned Power BI Row-Level SecurityIn a later phase, we redesigned the row-level security model and reduced security data volume by 90%, delivering significant performance improvements for all users.Empowering the Client's TeamWorking closely with the internal team, we established best practices for Databricks development and cost-efficient pipelines. Today, the team can independently maintain and further develop the platform. Utilized technologies Azure Databricks - Core platform for data processing and transformationDelta Lake - Storage layer for reliable and high-performance data processingAzure Data Factory and Azure Synapse Analytics (Pipelines) - Orchestration and management of data pipelines Azure SQL Server - Legacy data platform and source of the migrated processing logicAzure Analysis Services (Tabular) - Provision of semantic data modelsPower BI - Reporting and self-service analytics, including row-level security (RLS) Databricks Azure Data Factory Power BI The results 3× more frequent data refreshes: Three data refreshes per day instead of just one. 90% less security data: Faster, more responsive Power BI reports. Stability at scale: Reliable performance for thousands of users. Maintainable code: Clearly defined business rules instead of nested stored procedures. Cost-efficient operations: Right-sized compute resources. Self-sufficient team: Consistent standards for new pipelines. Best Practices for Your Databricks Migration Understand first, migrate second: Avoid carrying legacy issues over to the new platform. Eliminate redundancy: Ensure each piece of logic is implemented in only one place. Consider costs from the start: Right-size compute resources and schedule jobs efficiently. Optimise end-to-end: Consider data transformation, semantic models, reporting and security as a whole. Ensure knowledge transfer: Enable the internal team to work independently. Frequently Asked Questions About Databricks What is Databricks? Databricks is a cloud-based data lakehouse platform that brings together data processing, analytics and AI in a unified environment. On Microsoft Azure, it is available as Azure Databricks and uses Delta Lake as a reliable storage layer. Is migrating from Azure SQL Server to Databricks worth it? A migration is particularly beneficial when long processing times, growing data volumes or complex stored procedures limit data freshness. The key is to review and optimise the existing logic during migration rather than simply copying it. Can Databricks be integrated with Power BI? Yes. Databricks handles data processing and transformation, while Power BI provides reporting capabilities, including row-level security for thousands of users. Why it matters Migrating to Databricks is about more than just changing technology. It is the combination of a carefully planned migration, optimised business logic, improved semantic models and a redesigned security architecture that transforms a slow data platform into a scalable solution.Planning a Databricks migration or looking to modernise your data platform? Talk to our experts.More about Databricks Updated: 28.10.2026