Assisted business intelligence on performance of complex assets with taxonomy of real time systems

Abstract

Introduced herein are techniques that can create descriptive taxonomies of expected data streams and identify and associate each incoming data stream with the taxonomies automatically. The introduced techniques can significantly reduce the human intervention and efforts and hence the number of human errors in identifying and mapping signals. The introduced techniques can also automatically store values of the data streams and their corresponding taxonomies as facts and dimensions in a business intelligence (BI) data repository/warehouse. Doing so, the techniques create a BI data repository with various sets of logically nested dimensions and facts that can be used to analyze performances of various assets in petroleum service environment. Leveraging their similar hierarchical structures and elements, the techniques can expand and combine taxonomies and allow an end user to, not only analyze performances of assets in a specific rig, but across multiple rigs and projects, which were not possible before.