ABSTRACT
Web-based enterprise energy management (“EEM”) systems are delivering the information and control capabilities businesses need to effectively lower energy costs and increase productivity by avoiding power-related disruptions. However, the quality of energy decisions is directly affected by the quality of the data they are based on. Just as with CRM, ERP and other business intelligence systems, EEM systems have data quality issues, issues that can seriously limit the return on investment made in energy management initiatives.
Data quality problems result from a number of conditions, including the reliability and accuracy of the input method or device, the robustness of the data collection and communication topology, and the challenges with integrating large amounts of energy-related data of different types from different sources. This chapter describes how dedicated data quality tools now available for EEM applications can be used to help ensure that the intelligence on which an enterprise is basing its important energy decisions is as sound, accurate, and timely as possible.
