This paper will discuss an innovative approach to leverage data processed by AVEVA Predictive Analytics software. While AVEVA Predictive Analytics provides a robust dashboard for monitoring equipment performance, its operational focus limits its utility for high-level management.  To bridge this gap, we propose a comprehensive data processing pipeline that reprocesses predictive analytics data to map predictive model outputs to individual equipment units, tailoring the information for strategic management needs.

The core of this innovation lies in transforming operational data into strategic insights through the architecture of a data warehouse. Our methodology encompasses data ingestion, processing, and visualization stages.  It ensures that the information is not only accurate but also strategically relevant. The data ingestion phase involves collecting and integrating data from various sources, followed by data processing that cleans, transforms, and aligns the data with business objectives.  Finally, the visualization phase employs advanced dashboard techniques to present high-level insights suitable for strategic decision-making. 

Through that approach, we aim to provide high-level management with a comprehensive, clear, and actionable view of equipment performance, thus facilitating better decision-making and enhancing overall asset management.  This paper details the design and implementation of the data warehouse architecture, the processes involved in transforming predictive analytics data into strategic insights, and the benefits of this innovative solution in the context of Asset health and performance.