A data engineer building a sentiment analysis pipeline could use which AWS services?

Using Amazon S3, Amazon Transcribe, and Amazon Comprehend is an appropriate choice for building a sentiment analysis pipeline.

Amazon S3 serves as a durable storage solution where raw data, such as audio files or text, can be securely stored. This data can later be accessed by other services in the pipeline.

Amazon Transcribe is a service specifically designed for converting speech to text. In the context of a sentiment analysis pipeline, transcribing relevant audio data (like customer feedback or reviews) into text format is a critical first step. This enables the textual data needed for sentiment analysis to be derived from audio sources.

Amazon Comprehend is a natural language processing (NLP) service that can analyze the sentiment of the text generated by Amazon Transcribe. It utilizes machine learning to determine the sentiment behind the words, identifying whether the sentiment is positive, negative, neutral, or mixed, which is essential for understanding customer attitudes or opinions.

The combination of these three services—S3 for storage, Transcribe for converting audio to text, and Comprehend for analyzing the sentiment of that text—provides a comprehensive solution for sentiment analysis.