Analytics approaches include distributed analytics, real-time analytics, edge analytics, and machine learning. Which of the following tells the tale of edge analytics?

Select one:

a.

when is necessary in IoT systems to analyze data at scale, particularly when dealing with historical data that is too vast to be stored or processed by a single node. Data can be spread across multiple databases

b.

when high-volume IoT data streams is often performed in real-time, particularly if the stream includes time-sensitive data, where batch processing of data would produce results too late to be useful or any other application where latency is a concern

c.

when the data is pre-processed to filter out duplicates or to re-order, aggregate or normalize the data prior to analysis. This processing typically occurs at the point of acquisition.

d.

when analytics provides value as they can be used to track goals, create reports and insights, predict trends, and create simulations that are used to predict and optimize for specific outcomes.