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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with profiling a dataset of social media posts to understand public sentiment and identify key trends. The dataset contains millions of posts from various platforms, and your analysis must be scalable, cost-effective, and compliant with data privacy regulations. Which of the following approaches would BEST achieve a comprehensive analysis while addressing these constraints? Choose one option.
Explanation:
Option C is the most comprehensive and appropriate answer for profiling a dataset of social media posts under the given constraints. It combines natural language processing techniques for keyword and topic extraction with sentiment analysis, providing a holistic view of the data. Additionally, it emphasizes the importance of data quality and compliance, ensuring the analysis is both reliable and adheres to privacy regulations. While options A and B focus on specific aspects of the data, they overlook the broader context and data quality. Option D, while important, does not address the need for content analysis, making it less suitable for the task at hand.