Defining and deploying an Event has given us the ability to provide the following information:
- the start of each event period
- the end of each event period
- the duration of each event period
- associated attribute values that provide additional context for each event period (e.g. Orange, Apple, etc.)
Using the electricity usage example from earlier, if we have a Measure defined to retrieve the Filler’s electricity usage hourly, we can use the combination of the Measure and Event outputs to provide the following:
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Determine how much electricity was used by each Filler Run |
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Associate attribute values to the electricity used in each hourly period |
This overlay or slicing of Measure and Event information is extremely powerful and provides additional insight into your data. For example, questions like “how much electricity is used when we produce Apple juice?”, or “what is the average Filler Run electricity usage?”, can be answered.
The following timing diagram explains how the “slicing” of a Measure by an Event provides additional insight:
| TP = | Time Period (e.g. Hourly) |
| EP = | Event Period (e.g. Filler Run) with Product as attribute context (e.g. Apple, Orange, etc.) |
When the Hourly time periods and Filler Run event periods are overlaid, the overlay “slicing” of the time period becomes apparent.
TP is “sliced” into ①, ② and ③.
Slice ① of the hour is associated with Apple Juice production, slice ② is associated with no production, and slice ③ is associated with Orange Juice production.
The next hour is becomes slice ④ and is associated with Orange Juice production. Slice ⑤ of the next hour is also associated with Orange Juice production.
EP is made up of slices ③, ④ and ⑤.
The measure value for each of these slices (e.g. electricity usage) can be summed together to determine the total electricity usage for that Filler Run event period.
All of this information is contextualized and stored in the Flow Information Platform and available for analysis in charts and dashboards.