This strategy ignores any aggregated sum that includes missing data, even if only a single record is missing.
For example, a meter is added to a site, and four days later it starts recording energy consumption data. On a report or chart configured to aggregate the sum of all energy meters, the system ignores the aggregated sum for days 1–3 because the calculation for at least one meter contains missing data.
| Day | Meter 1 energy values | Meter 2 energy values | Aggregated values (sum) |
|---|---|---|---|
| 1 | - | 10 | - |
| 2 | - | 10 | - |
| 3 | - | 10 | - |
| 4 | 30 | 20 | 50 |
| 5 | 30 | 30 | 60 |
The aggregated sum ignores the fact that meter 2 recorded values of 10 for the first three days.
This strategy ignores only the values in the interval that are missing and accommodates the recorded values for the overall calculation.
For example, using the same meter as in the example of ignoring the series, the system aggregates the sum of all values ignoring only the missing values themselves.
| Day | Meter 1 energy values | Meter 2 energy values | Aggregated values (sum) |
|---|---|---|---|
| 1 | - | 10 | 10 |
| 2 | - | 10 | 10 |
| 3 | - | 10 | 10 |
| 4 | 30 | 20 | 50 |
| 5 | 30 | 30 | 60 |
The system counts Meter 2’s values for days 1–2.