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A Meter Data Management (MDM) system collects, validates and

integrates meter read information and in some cases other ancillary

and calculated information such as leak detection and high/low

consumption alerts. The MDM system consists of the communication

network to send and receive information and the necessary software

to communicate with other utility data systems such as a Customer

Information System (CIS).  MDM systems ensure that the communication network is healthy, and validate meter read data to ensure it meets the quality control requirements of the utility (e.g. the meter read is aligned with prior readings, and the meter read is coming from the correct transmitter and location).


MDM systems receive data from manual, Automated Meter Reading (AMR) technologies (e.g. drive-by, walk-by, handheld devices) and Advanced Metering Infrastructure (AMI) systems (e.g. radio, cellular devices).


The primary MDM functions include:


  • Triggering read activity through outbound read files

  • Collecting read upload files and import of read data

  • Generating read estimates


In general, MDM acquires meter reads for billing and analytics purposes. Specific goals of an MDM platform include:


  • Generate a “plausible read"


  • Perform VEE (Validation, Estimation, Editing)

    • Validate read against:

      • Absolute value

      • Previous reads

      • Rate of change of read

      • Same customer, same class, same Standard Industrial Classification (SIC) code or North American Industry Classification System (NAICS) code

    • Estimate a read if no “plausible read” exists

    • Notify of exceptions: 

      • No read

      • Non-numeric read

      • Leak

      • Tamper

      • Meter right sizing


  • Manage the infrastructure and communication network

    • Identify failing end points

    • Identify data collection issues (data collector coverage)

    • Identify failing meters






Meter Data Management systems allow utilities to:


  • Reduce the cost and time to gather, reconcile, and validate meter data from multiple collection systems

  • Provide enterprise-class scalability and performance to handle massive volumes of complex customer meter data

  • Lower the total cost of ownership of data management— from reducing upfront costs to minimising expenses for deployment and ongoing support

  • Provide higher quality data through the operation of a single, purpose-built data repository accessible across enterprise systems

  • Improve the reliability, security, and consistency of meter data for billing, operational systems, and analytics

  • Reduce errors associated with increased data collection and intervals.

  • Interface with a variety of analytical software

  • Improve operational efficiency by securing data that is audited and easily accessible to the enterprise

  • Insulate the utility’s business systems from the details of metering/meter reading in a multi-technology environment.

  • Develop programs from a new dynamic pricing model that encourages the efficient consumption of water






Meter Data Management systems require the ability to communicate both with the metering platform (AMI, AMR) and a means of moving information and data to other utility systems, primarily the Customer Information System. AMR-based MDM platforms typically reside on the computer system that receives information from the hand-held or drive-by systems. AMI-based MDM platforms require a means of receiving the data from data collectors, typically through an IP (internet protocol) connection. More advanced MDM platforms can receive data from AMR and AMI (as well as manual reads) and can allow for both types of metering technologies to work seamlessly.


MDM platforms can be both on-premise (loaded on a utility computer system) or hosted in a cloud environment.


MDM systems can communicate with CIS platforms through a number of data transfer protocols. This can be ETL (Extract, Transfer, Load) processes where files are downloaded and uploaded; or a direct integration with the CIS system where the data sources are connected via code and applications; or as web services where specific data is made available to the CIS platform.





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