Lof data refers to whether all supporting data points are available; for example, raw data that supports a predicted event or time series data that does not have gaps in it. Fill in the blank. Select one: a. Consistency b. Completeness c. Tim ness d. Reliability Provisioning is a key factor of device management. Which of the following best describes provisioning? Select one: a. When a new device is added to the system, the device should securely register itself with the device management service O O b. registering the metadata for the device c. Registering the device provides it with identity and credentials. d. All of the above Analytics approaches include distributed analytics, real-time analytics, edge analytics, and machine learning. Which of the following tells the tale of real-time analytics? Select one: a. when is necessary in loT 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 lot 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 o 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. 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 loT 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 O b. when high-volume lot 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. O 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