Meter data analytics

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Meter Data Analytics refers to the analysis of data emitted by electric smart meters that record consumption of electric energy.


Smart meters send usage data to the central head end systems as often as every minute from each meter whether installed at a residential or a commercial or an industrial customer. Utility companies sometimes analyze this voluminous data as well as collect it. Some of the reasons for analysis are

  1. to make efficient energy buying decisions based on the usage patterns,
  2. launching energy efficiency or energy rebate programs,
  3. energy theft detection,
  4. comparing and correcting metering service provider performance, and
  5. detecting and reducing unbilled energy.

This data not only helps utility companies make their businesses more efficient, but also helps consumers save money by using less energy at peak times. So, it is both economical and green. Smart meter infrastructure is fairly new to Utilities industry. As utility companies collect more and more data over the years, they may uncover further uses to these detailed smart meter activities. Similar analysis can be applied to water and gas as well as electric usage.


  • Oracle Utilities Meter Data Analytics Provides an efficient mechanism to extract high volume smart meter data out of meter data management systems in order to analyze the data without affecting the transactional system. It also provides comprehensive list of high level and detailed dashboards for usage patterns, head end system performance, meter installs, theft detection, vee exception analysis, and tamper event analysis.
  • Siemens Analytics Foundation Covers AMI health, outage and event analysis and load monitoring.
  • DataRaker Operates on a software as a service to provide analytics based on utilities data. Acquired by Oracle in 2012.[1]
  • Enoro Utilytics Cloud-based service offering customer insights, profitability overviews.[2]

According to a 2012 web posting, data that is required for complete meter data analytics may not reside in the same database. Instead, it might reside in disparate databases among various departments of utility companies.[3]

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