Abstract
Energy and utility companies are asset-intensive and often have aging infrastructure. They are also making a transition from time-based maintenance and heuristic decision-making to condition-driven maintenance and information-based decision-making. Achieving the objectives for infrastructure asset management requires integration of information from multiple heterogeneous data sources. This data resides in diverse and distributed systems of record, and these systems have proprietary data formats, data semantics, and data stewardship processes. It is challenging to organize these varieties of data sources into an integrated system to enable development and deployment of a wide variety of advanced asset analytics to support an effective asset management strategy. In this paper, we report on an integrated analytics system that addresses challenges in 1) organizing the data sources into a coherent integrated data model, 2) providing core capability of history reconstruction and other data services, and 3) provisioning to handle the large volume of historical data.
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