https://store-images.s-microsoft.com/image/apps.57056.956d3a12-c759-4c97-827c-942f86ef940d.e6216902-085d-4e74-b743-ea28a14c4fcf.21868101-4b0c-43f0-851d-b20d97ea06c4

Fabric Graph Manufacturing Offering with Power BI

Mandelbulb Technologies Private Limited

Fabric Graph Manufacturing Offering with Power BI

Mandelbulb Technologies Private Limited

Integrated MES solution for chemical and manufacturing process hierarchy management with Fabric & BI

This solution represents an advanced analytics platform, specifically developed to tackle the intricate hierarchies present in chemical and manufacturing workflows. At its core, the system utilizes the powerful in-memory graph capabilities of KQL (Kusto Query Language), enabling the analysis and management of complex relationships and dependencies within production processes. This high-performance querying approach allows for the swift traversal of connected data points, ensuring that users can identify trends, bottlenecks, and opportunities with unprecedented speed and accuracy.


Built on Microsoft's Fabric for a seamless and scalable user experience, the platform facilitates interaction with a vast array of data inputs and operational variables. It allows for the dynamic manipulation of data models and the creation of custom workflows suited to the unique requirements of manufacturing and chemical production environments.

Visualization is a key feature of this solution, with Microsoft Power BI integration at the forefront. Power BI's robust visualization tools are leveraged to present insightful data analytics in an intuitive format. Users can create custom dashboards and reports, offering them a clear view of the production landscape and enabling data-driven decisions that can drive efficiency and productivity gains.


The combination of KQL's in-memory graph processing with Power BI's visualization excellence creates a powerful tool for manufacturers and chemical producers. This platform is not just about managing data but transforming it into a strategic asset that can lead to optimized operations, cost savings, and improved output quality.

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