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Technologies and customer needs are changing rapidly and traditional analysis processes are quickly reaching their limits. Our industrial customer has an impressive data history with information dating back up to 200 years. However, despite structured management, much of this data remains in silos and is not actively used. Valuable potential for data-based decisions and innovation therefore remains untapped.
With Microsoft Fabric, we are creating a central, integrated platform that breaks down these data silos and combines all data sources into a single, unified data model - seamlessly and scalably. Teams gain self-service access to consolidated data and can therefore make faster, more secure and more customer-oriented decisions. Particularly with regard to AI initiatives, Fabric creates the necessary basis for real-time analyses, machine learning and automated insights, all in a toolset that is based on existing Microsoft infrastructure. The aim is to use Microsoft Fabric to finally harness existing data values, create transparency and sustainably accelerate innovation.
How can data silos be reduced?
How can historical and current data sources be linked in a meaningful way?
How is a basis for AI initiatives and innovations created?
Together with the client, we identify goals, challenges and priorities. In structured sessions, we develop specific use cases and evaluate them in terms of costs, benefits and technical feasibility with a focus on analytics, information access and AI applications.
We gain an overview of the existing data landscape, including historical data, current systems and silo structures. Relevant source systems are prioritized for integration into Fabric, e.g. ERP, CRM, IoT or Excel-based reports.
Based on the use cases and data sources, we implement a scalable Microsoft Fabric architecture. We configure the relevant modules such as Data Factory, OneLake, Synapse, Power BI and set up a consistent governance and security model.
We load the prioritized data into Microsoft Fabric, build semantic models and develop dashboards, reports or ML pipelines. The first quick wins are implemented productively, e.g. automated reports or AI-supported analyses.
We train internal teams in the use of Fabric and anchor self-service analytics in everyday life. At the same time, we scale the architecture to other use cases and business areas, always in line with the developed priority model.
The project at our industrial customer aims to harness data as a strategic asset and pave the way for AI-based innovations. For this reason, a central data platform based on Microsoft Fabric was set up, which significantly simplifies access to information and systematically breaks down silo structures. The integrated use of OneLake, Synapse and Power BI enables the teams to make informed decisions more quickly and implement data-driven use cases efficiently. This creates a scalable infrastructure that actively supports future growth and technological development.
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