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Answer: Utilize Azure Databricks with Apache Spark for real-time processing and analysis of streaming data, and employ Azure Data Factory to seamlessly integrate the analytics results with the Microsoft Fabric environment for reporting and visualization.
Option B is the correct answer because it provides a comprehensive solution that leverages Azure Databricks for efficient real-time processing and analysis of streaming data using Apache Spark. The integration with the Microsoft Fabric environment through Azure Data Factory ensures that the solution is scalable, cost-effective, and compliant with data governance policies. Option A is limited by its reliance on Azure SQL Database for storage, which may not be the most scalable or cost-effective option for large volumes of streaming data. Option C's use of Azure Functions for processing may not be as efficient or scalable as Apache Spark for complex analytics. Option D focuses on visualization with Power BI but lacks a detailed approach for processing and integrating the data within the Fabric environment.
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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with designing a solution that supports real-time analytics and reporting for streaming data from IoT devices. The solution must integrate seamlessly with the existing Microsoft Fabric environment, ensuring scalability, cost-effectiveness, and compliance with data governance policies. Which of the following options best describes a comprehensive approach to achieve these objectives? (Choose one option)
A
Deploy Azure Stream Analytics to process streaming data in real-time, store the processed data in Azure SQL Database for reporting, and use Azure Data Factory to integrate the data with the Microsoft Fabric environment.
B
Utilize Azure Databricks with Apache Spark for real-time processing and analysis of streaming data, and employ Azure Data Factory to seamlessly integrate the analytics results with the Microsoft Fabric environment for reporting and visualization.
C
Ingest streaming data through Azure Event Hubs, process and analyze the data in real-time using Azure Functions, and then integrate the insights with the Microsoft Fabric environment via custom APIs.
D
Connect and manage IoT devices using Azure IoT Hub, analyze the streaming data with Azure Time Series Insights for real-time analytics, and visualize the insights within the Microsoft Fabric environment using Power BI.