Description | This analysis shows the percentage of normal intervals that were received in the selected month. |
Purpose | This analysis indicates the quality of the interval meter readings being handled by the utility. If there is a dip in the percentage of normal (not missing or estimated or otherwise inferior) interval readings, it might mean that corrective actions will have to be undertaken by the utility. An increase in non-normal readings may indicate that a group of AMI devices are beginning to fail. |
Representation | The gauge shows the percentage of normal intervals that have been received, using different colors to denote how the business users perceive the calculated result. The needle movement in the gauge towards yellow or red indicates a need to pay more attention on the interval scenarios. Hover over the gauge for specific values. Note: The ranges for green, yellow, and red can be configured. The table displays the count of normal intervals, its percentage against the total, and the total interval count for the selected month. |
Drill Down | The gauge drills down to the Quality dashboard page for the same time period. |
Source Object | Quality Count Fact |
OAS Subject Area | MDM - Quality Count |
Metrics | Normal Interval %, Normal Count, Total Count |
Description | This analysis shows the percentage of on-time intervals that were received in the selected month. |
Purpose | This analysis indicates the timeliness of the interval meter readings received by the utility. If there is a dip in the percentage of interval readings received on time, it might mean that corrective actions will have to be undertaken to correct the late arriving measurements. The analysis is especially useful when utilities are determining if the head end systems are meeting their service level agreements (SLA) for on time reading delivery. |
Representation | The gauge shows the percentage of on-time intervals, using different colors to denote how the business users perceive the calculated result. The needle movement in the gauge towards yellow or red indicates a need to pay more attention on the on-time interval scenarios. Hover over the gauge for specific values. Note: The ranges for green, yellow, and red can be configured. The table displays the count of on-time intervals, its percentage against the total, and the total quantity for the selected month. |
Drill Down | The gauge drills down to the Timeliness dashboard page for the same time period. |
Source Object | Timeliness Count Fact, Timeliness Quantity Fact |
OAS Subject Area | MDM - Timeliness Count, MDM - Timeliness Quantity |
Metrics | On-Time Intervals %, On-Time Count, On-Time Quantity |
Description | This analysis shows a breakdown of normal intervals by the selected segment. The data is shown for the selected month. |
Purpose | This analysis indicates the quality of the interval meter readings received by the utility. If there is a dip in the percentage of normal interval readings, it might mean that corrective actions will have to be undertaken by the utility. |
Representation | The View By drop-down slices the details by head end system, device type, manufacturer, market, service provider, usage calculation group, city, or postal code. The table shows the normal %, normal count, and the total count of intervals for the selected segment. |
Drill Down | The <segment> column link drills down to the Quality dashboard page for specific details. |
Source Object | Quality Count Fact |
OAS Subject Area | MDM - Quality Count |
Metrics | Normal Interval %, Normal Count, Total Count |
Description | This analysis shows a breakdown of on-time intervals by the selected segment. The data is shown for the selected month. |
Purpose | This analysis indicates the timeliness of the interval meter readings received by the utility. If there is a dip in the percentage of interval readings received on time, it might mean that corrective actions will have to be undertaken by the utility. |
Representation | The View By drop-down slices the details by head end system, city, device type, market, service provider, usage calculation group, manufacturer, or postal code. The table shows the on-time %, on-time count, and the on-time quantity for the selected segment. |
Drill Down | The <segment> column link drills down to the Timeliness dashboard page for specific details. |
Source Object | Timeliness Count Fact, Timeliness Quantity Fact |
OAS Subject Area | MDM - Timeliness Overview |
Metrics | On-Time Interval %, On-Time Count, On-Time Quantity |
Description | This analysis shows the distribution based on the quality of the measurements for the selected month. It displays the count for each quality category as well as the percentage of that count out of the entire total. |
Purpose | Using this tool, business users can analyze the distribution of normal and non-normal measurements for the selected period. |
Representation | The pie chart shows the distribution of normal measurements as a percentage of total measurements. The table shows the details of the measurements segmented by quality categories. |
Drill Down | No drill down |
Source Object | Quality Count Fact |
OAS Subject Area | MDM - Quality Count |
Metrics | % of Total |
Description | This analysis shows the count of non-normal interval data against each quality category. |
Purpose | Using this tool, business users can analyze the non-normal interval details on a daily basis and identify the respective quality categories. A large number of non-normal measurements may signify a problem with the metering system or other application issues. |
Representation | The stacked bar graph shows the count of non-normal interval data per month segmented by quality category. The X-axis represents the month and year. The Y-axis represents the interval percentage. Hover over the bars for specific details. The table shows the count and percentage of non-normal intervals for the previous 15 months. |
Drill Down | The Month column link drills down to view the daily details. |
Source Object | Quality Count Fact |
OAS Subject Area | MDM - Quality Count |
Metrics | % of Total |
Description | This analysis shows the count of various quality measures for the selected segments. The data is shown for the selected time period. |
Purpose | This analysis provides a summarized view of the various quality measures, such as normal, estimated, etc. It allows users to “slice” the database to perform custom data analysis. The three “View By” selections allow users to define the viewing hierarchy. Once the selection is made, the user is presented a summary of the data. They can then drill into the details to see the particular device/service points in question. |
Representation | The View By drop-down slices the details by head end system, manufacturer, geo code, city, device type, market, service provider, usage calculation group, or postal code. Note: You can select a combination of three segments. The table displays the count of quality measures and the respective percentages for the selected segments. |
Drill Down | No drill down |
Source Object | Quality Count Fact |
OAS Subject Area | MDM - Quality Count |
Metrics | Normal Count, Estimated Count, User-Edited Count, No Measure / IMD No IMD Count, No Measure / IMD Exists Count, No Read – Outage Count, % of Total |
Description | This analysis shows the distribution of AMI interval timeliness in the selected month. |
Purpose | Using this tool, business users can identify what percentage of interval readings are arriving late. This analysis can be further classified into various late buckets as configured in the source system. |
Representation | The pie chart shows the distribution of AMI interval timeliness (on time, < 24 hours late, 24-48 hours late, 48+ hours late, and missing). The table displays the count and percentage total of the AMI intervals. |
Drill Down | No drill down |
Source Object | Timeliness Count Fact, Timeliness Quantity Fact |
OAS Subject Area | MDM - Timeliness Overview |
Metrics | On-Time Count, Late Count, Missing Count Note: Late Count measures are dynamically calculated as per the late bucket configuration in the source system. |
Description | This analysis shows the monthly trend of the late AMI intervals over time. The data is shown for the previous 15 months. |
Purpose | Using this tool, business users can monitor the trends, in the quantity, of late arriving interval meter reads. They can also analyze the sub trends based on the various late buckets as configured in the source system. |
Representation | The stacked bar graph shows the trend of late AMI intervals over time. The X-axis represents the month and year. The Y-axis represents the late AMI interval count. Hover over the bars for specific details. |
Drill Down | The Month column link drills down to view the daily details of intervals for the selected month. |
Source Object | Timeliness Count Fact, Timeliness Quantity Fact |
OAS Subject Area | MDM - Timeliness Overview |
Metrics | Late Count, Late Quantity Note: Late Count measures are dynamically calculated as per the late bucket configuration in the source system. |
Description | This analysis shows the count of various timeliness measures for the selected attributes. The data is shown for the selected time period. |
Purpose | This analysis provides a summarized view of the various timeliness measures. Business users can view the data by various combinations. The analysis allows users to “slice” the database to perform custom data analysis. The three “View By” selections allow users to define the viewing hierarchy. Once the selection is made, the user is presented a summary of the data. |
Representation | The View By drop-down slices the details by head end system, manufacturer, geo code, city, device type, market, service provider, usage calculation group, or postal code. The table shows the count and percentage total of the AMI intervals in the selected attributes. |
Drill Down | No drill down |
Source Object | Timeliness Count Fact, Timeliness Quantity Fact |
OAS Subject Area | MDM - Timeliness Overview |
Metrics | On-Time Count, On-Time Quantity, Late Count, Missing Count Note: Late Count measures are dynamically calculated as per the late bucket configuration in the source system. |
Description | This analysis shows the distribution of estimated and user-edited measurement quantity per estimated and user-edited measurement count per month. |
Purpose | This analysis allows users to see the estimated quantities by month, if the estimates are trending up or down. |
Representation | The stacked bar graph shows the estimated and user-edited quantities. The lines on the graph represent the estimated and user-edited count. The X-axis represents the month and year. The Y1-axis represents the estimated and user-edited quantities, while the Y2-axis represents the estimated and user-edited count. Hover over the bars for specific details. |
Drill Down | No drill down |
Source Object | Quality Count Fact |
OAS Subject Area | MDM - Quality Overview |
Metrics | Estimated Quantity, User Edited Quantity, Estimated Count, User Edited Count, % of Total |