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News29/05/2012Accurate data leads to better energySoftware tools help to ensure data quality As energy demand continues to increase across the globe, more and more organizations deploy enterprise energy management (EEM) systems to lower energy-related costs, and to ensure power reliability. These systems consist of a network of energy meters located within a facility or series of facilities as well as software that manages the process of analysing the data gathered by the meters. The key factor that differentiates one enterprise energy management system from another is the quality of the energy data gathered and the process by which the data is utilized to make decisions. Issues such as power failures, problems with metering equipment, communication interruptions, or human error can impact the quality of energy data. Often the problems can go on unnoticed for a significant length of time. The impact of poor data can be costly, including missed opportunities to reveal energy waste, to leverage lower utility pricing, or to avoid an emissions fine from a regulating authority. Poor data quality can cause misleading energy trend reports, inaccurate billing reports, and a reduced confidence in critical business decisions. New tools can help The good news is that new data quality tools are available for industrial, commercial, and institutional energy consumers to ensure the intelligence delivered by their enterprise energy management systems is accurate, complete, and timely. The quality of all energy-related data coming into the system is first validated based on predefined internal data quality standards. Then specific tools correct for errors or gaps so that data is cleansed before it is analysed, reported, or otherwise put into action. For example, exact duplicates are typically deleted and automated estimation tools allow erroneous data to be replaced. Best practices A comprehensive data quality solution should be:
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