Descriptive Analytics > Scenarios for Use
Scenarios for Use
Use Cases for Descriptive Analytics Services
The output of Descriptive Analytics monitoring or calculation services can be used in a number of ways. The following scenarios represent some typical uses for the output:
Visualizing Data – Provide maintenance technicians a visual format to observe descriptive analytics from their asset data. They will gain insight into the operating conditions of the asset and be able to investigate issues quickly. How? Configure an event that will call statistical monitoring or calculation services once per shift to compute the minimum, median, and maximum values of a signal on a specific asset. Display the results in a mashup so that maintenance technicians can observe the continuous pattern of the signal and respond to any issues.
Creating Alerts – An application engineer can use descriptive analytics to raise an alert if the value of a signal or property falls above or below a specified level. How? Configure an event that will trigger a statistical monitoring or calculation service every 30 minutes. The service will compute the median on a signal and check whether the median is within an expected range. Configure an alert to react when that median is outside of the expected range.
Generating Transformed Data – An application engineer can use descriptive analytic services to perform commonly-used calculations on raw data. These services can be built into a solution so that output from the services is used as input for advanced analytics processing. How? Configure an event that will trigger a statistical calculation service every 30 minutes to compute FFT on a vibration signal. Add the results to the ThingModel in ThingWorx Platform (for example, on a new property). This data can then be used every hour to make a prediction about whether the asset in question is likely to malfunction.
Descriptive Analytics Services or Property Transforms?
Both Descriptive Analytics Services and Property Transforms provide a way to implement common statistical calculations on property data. However, these tools are designed to handle different scenarios and use different computing resources. While Descriptive Analytics provides on-demand services in a batch scenario, Property Transform services derive value from streaming data as it enters ThingWorx. That said, in some scenarios, it can be difficult to decide which approach is more appropriate.
For an in depth comparison of the two tools, see the PTC Community article entitled Descriptive Services or Property Transforms, which approach to use? The article examines the similarities and differences between the two approaches and provides guidelines for choosing the right approach for a given scenario.
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