To include a sentiment score for documents in an index, what is the recommended action?

The recommended action to include a sentiment score for documents in an index is to add the built-in Sentiment skill to the skillset. This option is correct because the built-in Sentiment skill in Azure Cognitive Search is specifically designed to analyze text and generate sentiment scores, which can be seamlessly integrated into the skillset of an Azure Search pipeline. This built-in option is efficient, requiring minimal setup compared to creating custom skills and allows for rapid deployment.

Utilizing the built-in Sentiment skill also ensures compatibility with the Azure ecosystem and often results in better performance and maintenance since it is a pre-optimized solution. It simplifies the process of extracting sentiment from documents by providing a straightforward way to utilize existing Azure technology without the need for extensive coding or integration work that might be necessary with custom solutions.

In contrast, creating a custom skill using Azure Machine Learning or building a custom skill to call the Text Analytics service could require more time and resources, making it less ideal for immediate implementation when a built-in feature already serves the purpose effectively. While third-party sentiment analysis tools can offer specialized insights, they may introduce additional complexity in terms of integration, data privacy concerns, and dependability on external services, making them less desirable compared to an integrated Azure solution.