Why Microsoft Fabric?

A leading provider of fleet management, grappling with dispersed data sources, slow query performance, and rising infrastructure costs, recognized that its existing data and analytics infrastructure was no longer adequate. To address these challenges, the company embarked on a strategic transformation to modernize its systems, streamline data access, and enhance decision-making and business agility. Partnering with Visionaize, the company built a data platform powered by Microsoft Fabric – a solution designed for scalability, automation, and real-time analytics.

This transformation delivered significant improvements, including up to a 22% reduction in data consolidation time and 15-20% faster data analysis, ultimately empowering the organization with enhanced operational efficiency and business agility.

• 22% faster consolidation
• 15–20% faster analytics
• Higher operational efficiency

A large international port handling high shipping volumes aimed to become a data-led organization but found its data management and storage needed a major overhaul. Data was fragmented across multiple operational systems, each providing different and sometimes inconsistent views, making it hard to access, use, and maintain accurate information. The port also struggled to synchronize critical reference data across systems, limiting reliable insights on vessels, ports, and other core entities. In parallel, the port sought to reduce high energy costs and improve sustainability, but energy meter data was scattered across systems and providers, preventing a single source of truth for consumption and performance tracking.

Visionaize built a Microsoft Fabric based Data Lake to store all fragmented data into a single data repository enabling the port to take decisions in real time based on the consolidated and contextualized data. This significantly improved and insights about vessel movement, shipping and container information, additionally it was able to identify areas of the port that could leverage renewable energy options to reduce costs and their carbon footprint.

• Single data repository
• Real-time decision making
• Energy cost optimization

A leading automotive manufacturer produces critical components across technologies ranging from conventional combustion engines to advanced electric powertrains. While production and maintenance teams followed defined workflows, data collection remained largely manual. Production staff had to visit machine consoles, collect parts and downtime data, and enter it into a central PC, taking about five minutes per shift, with tooling changes adding more effort. Maintenance teams printed SAP work orders, carried them to machines, diagnosed and fixed issues, and then updated SAP, spending around 15 minutes per task. A unified, scalable digital platform was needed to connect data sources, improve transparency, and streamline processes across all plants.

Leveraging the Microsft Azure & Fabric capabilities they are able to collect production machine data with Azure IoT connectivity components, store it in Azure Data Lake, and then use Azure Data Explorer to prepare and provide it for analysis. This transformation has enabled them to consolidate data from 12 plants and helped to increase efficiency by replacing manual processes with automated data driven workflows.

• 12 plants consolidated
• Manual work eliminated
• Efficiency significantly improved