Reference Data for IoT Sensor Metadata | Microsoft DP-203 Exam Prep

What Services Can Be Used as Input for IoT Sensor Metadata?

Question

A famous IOT devices company collects the metadata about its sensors in the field in reference data.

Which of the following services can be used as input for this type of data? (Multiple Choice)

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D.

Correct Answers: A and B.

Reference data is a fixed data set that is static or, in some cases, changes slowly.

Here the metadata values of sensors are slowly changing and thus can be considered as reference data as the question tells.

Azure blob storage can ingest this type of data, in which the data is modeled to be a sequence of blobs in ascending order of the date/time specified in the blob name.

Similarly, Azure SQL also can intake reference data.

In this case, the data is retrieved by Job in stream analytics and is stored with snapshot memory for further processing.

Options A and B correct: Azure SQL and Blob storage are supported input services for reference data.

Options C and D incorrect: Azure Event Hub and IoT hub are not supported.

To know more, please refer to the docs below:

All of the services listed can be used as input for the metadata about IoT devices, but they differ in their use cases and capabilities. Here is a detailed explanation for each of the options:

A. Azure SQL: Azure SQL is a fully managed relational database service that is built for mission-critical applications. It provides a fully managed and highly available database engine with support for high-performance transactions, efficient queries, and built-in security. It's typically used for structured data, such as application data or transactional data, rather than unstructured data like metadata about IoT sensors. Therefore, while Azure SQL is a good option for storing and managing application data, it's not the best fit for storing IoT metadata.

B. Blob Storage: Blob storage is a massively scalable and durable object storage service for unstructured data, such as images, videos, and log files. It provides a simple, cost-effective way to store large amounts of data, and it supports multiple access tiers, including hot, cool, and archive. Blob storage is ideal for storing unstructured data such as the metadata about IoT sensors.

C. Azure Event Hub: Azure Event Hub is a highly scalable data streaming service that enables real-time data ingestion and processing. It is designed for high throughput and low latency, making it ideal for IoT applications where real-time data is critical. Event Hub is used to ingest large volumes of data from multiple sources and store the data for further processing or analysis. It provides a highly available, fault-tolerant data pipeline for event data, and it integrates well with other Azure services, including Stream Analytics and Azure Functions.

D. Azure IoT Hub: Azure IoT Hub is a fully managed service that enables secure and scalable communication between IoT devices and cloud applications. It provides a bi-directional communication channel between devices and cloud services, and it supports a variety of protocols, including MQTT, AMQP, and HTTP. IoT Hub provides device management, security, and telemetry, and it integrates with other Azure services, including Stream Analytics and Azure Functions. It is designed specifically for IoT applications and is a good option for managing and processing metadata about IoT devices.

In summary, the best options for storing metadata about IoT devices are Blob Storage, Azure Event Hub, and Azure IoT Hub. Blob storage is a good option for unstructured data, while Event Hub and IoT Hub are designed specifically for IoT applications and offer more functionality and integration with other Azure services. Azure SQL is more suited for structured data such as application data or transactional data rather than unstructured data like metadata about IoT sensors.