You work for an automotive manufacturer which already has an Azure IoT solution in place. The solution collects millions of data from thousands of field equipment like presses, welding robots, conveyors etc. The quality department wants to add an improvement which can provide them with near real-time visualization of the trends, by asset categories. You are suggested to use Time Series Insights models. 
Which is not an advantage of TSI models?

Answer options:

A.They can be used to add computational rules
B.They can be used to enrich the time series data
C.They can organize time series data into hierarchies
D.They can be used to apply ML models

Correct Answer: D
Option A is incorrect because TSI models have a Types feature which allows for defining variables and to add computational rules to them.
Option B is incorrect because both the Hierarchies and the Types features of the TSI models enable enrichment of time series instances, either by organizing them into hierarchies or adding derived computed information to the raw data.
Option C is incorrect because TSI model hierarchies organize instances by specifying names of properties and their relationships.
Option D is CORRECT because Time Series Models don’t have any relations to ML models.
Diagram: 

References: 

https://docs.microsoft.com/en-us/azure/time-series-insights/how-to-provision-manage
https://docs.microsoft.com/en-us/azure/time-series-insights/overview-use-cases
https://docs.microsoft.com/en-us/azure/time-series-insights/how-to-plan-your-environment