This analysis shows the percentage of normal intervals that were received in the selected month.

 

Note: This analysis is configured to select a default aggregation type from the database. If it has to be based on a different aggregation type, the appropriate aggregation type as available in the source Oracle Utilities Meter Data Management application needs to be set.

This analysis indicates the quality of the interval meter readings being handled by the utility. It is often used to determine the quality of the data sent by the AMI head end systems or other sources. If the percentage of normal interval readings (not estimated, missing, etc.) is low, it might mean that corrective actions will have to be undertaken by the utility. Business users are not limited to viewing data by head end system. Other attributes, such as device type, can also be selected.

The gauge shows the percentage, 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.

Drill Down

The gauge drills down to the Overview dashboard page in the Performance dashboard for specific interval details.

Source Object

Quality Count Fact

OAS Subject Area

MDM - Quality Count

Metrics

Normal Interval %

This analysis shows the percentage of on-time intervals that were received in the selected month.

 

Note: This analysis is configured to select a default aggregation type from the database. If it has to be based on a different aggregation type, the appropriate aggregation type as available in the source Oracle Utilities Meter Data Management application needs to be set.

This analysis indicates the timeliness of the interval meter readings received by the utility. It is used to determine the timeliness of the data sent by the AMI head end systems or other sources, which allows customers to see if the metering system is delivering meter readings on time. Business users are not limited to viewing data by head end system. Other attributes, such as device type, can also be selected.

The gauge shows the percentage, 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.

Drill Down

The gauge drills down to the Overview dashboard page in the Performance dashboard for specific interval details.

Source Object

Timeliness Count Fact, Timeliness Quantity Fact

OAS Subject Area

MDM - Timeliness Overview

Metrics

On-Time Intervals %

This analysis provides a snapshot of unreported usage for more than 30 days.

 

Note: This analysis is configured to select a default Unit Of Measure value from the database. If it has to be based on a different UOM value, the appropriate UOM code as available in the source Oracle Utilities Meter Data Management application needs to be set. It is based on how customers might want to customize the analysis.

Business users can see consumption that has not yet been sent to the billing system (bill determinants). The analysis indicates the potential revenue that is yet to be realized by the utility.

The bar graph shows the unreported usage quantity (in Kilowatt-Hours) per number of service points per month. The X-axis represents the month. The Y1-axis represents the unreported usage quantity, while the Y2-axis represents the number of service points.

 

The line on the bars shows the number of service points for which the unreported usage quantity is being displayed. Hover over the bars for specific values.

Drill Down

The graph bars drill down to the Overview dashboard page in the Usage Summary dashboard for specific usage details in that month.

Source Object

Unreported Usage Analysis Snapshot Fact

OAS Subject Area

MDM - Unreported Usage Analysis Snapshot

Metrics

Usage Quantity (KWH)

This analysis shows how the VEE exceptions are distributed across each exception type in the selected month.

Business users can identify the top five exception types that occurred during the VEE processing of the raw initial measurement data. The analysis serves as a starting point to analyze why these exceptions occur and any patterns within them.

The pie chart shows the distribution of VEE exception types in the selected month. It shows only the top five exception types and merges the remaining exception types into one slice. If there are fewer than five, all the exceptions are shown as individual slices.

Drill Down

The pie chart drills down to the Overview dashboard page in the VEE Exceptions dashboard for specific details.

Source Object

VEE Exception Fact

OAS Subject Area

MDM - VEE Exception

Metrics

% of Total

This analysis shows the actual heating and cooling degree days, and also the total usage/load for the previous three months.

 

Cooling Degree Days is normally the number of degrees the average daily temperature is above the baseline (65F) on hot days. Heating Degree Days is the number of degrees below 65F on cold days. Daily values are added together to get a monthly value. Degree days are configurable.

 

Note: This analysis is configured to select a default aggregation type from the database. If this analysis has to be based on a different aggregation type, the appropriate aggregation type available in the source Oracle Utilities Meter Data Management application has to be set.

This analysis shows the relationship between usage and degree days. Degree days are used to identify when weather sensitive premises began using air conditioning or heating. Both heating and cooling degree days can be shown. For temperature sensitive premises, the energy consumed should correlate with the degree days.

The bar graph shows the heating and cooling degree days in each month. The line on the graph shows the total usage in each month.

 

Electric kWh 60min (Measured Quantity) represents the aggregator measuring component based on which the consumption is filtered.

 

The X-axis represents the month. The Y-axis represents the degree days, along with the total usage. Hover over the bars for specific details.

Drill Down

The graph drills down to the Degree Days dashboard page for specific usage details.

Source Object

Measured Quantity Fact

OAS Subject Area

MDM - Measured Quantity

Metrics

Bar - Heating and cooling degree days

Line - Usage

This analysis shows the total number of initial measurements that resulted into exceptions. The data is shown for the selected month.

 

% of Total = Sum ((Distinct IMD count with exceptions) /Sum (Distinct IMD count)) * 100

This analysis serves as a health indicator of raw initial measurement data. If the needle points to red, it means that more than an acceptable quantity of initial measurement data is resulting in exceptions. That warrants a quick corrective action by the utility. A high number of exceptions can be caused by numerous occurrences, such as head end system failure, interface failure (devices not setup), VEE rule tolerances are set too tightly, etc.

The gauge shows the percentage of initial measurements that resulted into exceptions in the current month. It uses different colors to denote how the users perceive the calculated result.

 

The needle movement in the gauge towards yellow or red indicates a need to pay more attention on the exceptions.

 

Note: The ranges for green, yellow, and red can be configured.

Drill Down

The gauge drills down to the Overview dashboard page in the VEE Exceptions dashboard for specific exception details.

Source Object

VEE Exception Fact

OAS Subject Area

MDM - VEE Exception

Metrics

% of Total

This analysis shows the number of devices (as a percentage of the total) that were sending measurement data and then stopped sending for some reason. The data is displayed for the selected month.

Using this analysis, business users can analyze devices that have stopped recording measurements. They can also see how long this has been a problem. This is often an indicator that a meter has “died” and needs to be replaced.

The pie chart shows the distribution of devices (that stopped sending measurements) across various aging buckets in the selected month.

Drill Down

The pie chart drills down to the Devices without Measurements dashboard page for specific device measurement details.

Source Object

Service Point Snapshot Fact

OAS Subject Area

MDM - Service Point Snapshot

Metrics

Devices (shown as % distribution among the buckets)

This analysis shows how the device activities (that are both open and completed) are distributed as a percentage of total. The data is shown for the selected month.

Using this tool, business users can identify the activity types that are performed by the utility. An activity is a generic object used to represent AMI commands, outage processes, service orders, etc. An activity is often used to represent a business process.

The pie chart shows the distribution of device activities as a percentage of the total.

Drill Down

The pie chart drills down to the Overview dashboard page in the Device Activities dashboard for specific device activity details.

Source Object

Device Activity Fact

OAS Subject Area

MDM - Device Activity

Metrics

Count of Device Activity (Shown as % of Device Activities distribution for all Activity Types)

Tamper events are the types of device events defined in the system to indicate that a particular meter/device installed in the field has been tampered for illicit purposes.

 

This analysis shows the count of tamper device events based on the event category. The data is shown for the selected month and previous two months.

 

Note: To view the data, this analysis should be configured to set the appropriate code for tamper events to be shown. The appropriate Event Category code as available in the source Oracle Utilities Meter Data Management application has to be set in the filter section.

With this analysis, business users can monitor device tampering trends. A large volume of such events, in the graph, could warrant immediate corrective action by the utility to prevent device tampering which contributes to revenue loss.

The bar graph shows the tamper event count for each month. The X-axis represents the event count. The Y-axis represents the month and year. Hover over the bars for specific values.

Drill Down

The graph bars drill down to the Overview dashboard page in the Device Activities dashboard page for more details.

Source Object

Device Event Fact

OAS Subject Area

MDM - Device Event

Metrics

Events

A device is active if it reads and sends measurement data to the collection devices.

 

This analysis shows the total number of smart devices that are active in a month. The data is shown for the selected month and previous two months.

Using this tool, business users can monitor smart devices installed in the field.

The bar graph shows the active installed devices in each month. The X-axis represents the device count. The Y-axis represents the year and month. Hover over the bars for specific values.

Drill Down

The graph drills down to the Device Status page in the Devices & Installations dashboard.

Source Object

Service Point Snapshot Fact

OAS Subject Area

MDM - Service Point Snapshot

Metrics

Installed Devices