Describe features of Natural Language Processing workloads on Azure →mediumMultiple ChoiceObjective-mapped
AI-900 Practice Question: Describe features of Natural Language Processing workloads on Azure
A customer support team wants to automatically analyze customer emails to determine if the sentiment is positive, negative, or neutral. Which Azure service should they use?
⚠ Common exam trap
Test-takers frequently confuse Text Analytics with other NLP services like Translator or QnA Maker, mistakenly thinking any 'language' service can do sentiment analysis, but only Text Analytics has the specific pre-built sentiment model.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Text Analytics
The Text Analytics service (part of Azure Cognitive Services) provides pre-built sentiment analysis, which can classify text as positive, negative, or neutral. This directly matches the requirement to automatically analyze customer emails for sentiment without needing to build custom machine learning models.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Speech
Why it's wrong here
Azure Speech (Speech service) is focused on processing spoken audio—it performs speech-to-text, text-to-speech, speech translation, and speaker verification. Although it can transcribe support calls, it is not a general-purpose text sentiment analyzer; sentiment classification of the transcribed or written text is better handled by a dedicated language model such as Text Analytics.
- ✗
Translator
Why it's wrong here
Azure Translator is a machine translation service that converts text or documents between languages. It can detect the source language but does not evaluate emotional tone or assign sentiment labels; the output is linguistically equivalent text, not an analysis of whether a customer is happy or frustrated. Sentiment analysis requires a cognitive service specifically trained for that task.
- ✓
Text Analytics
Why this is correct
Azure Text Analytics (now a feature of the Azure Language service) provides pre-built natural-language processing capabilities, including sentiment analysis, opinion mining, key-phrase extraction, and entity recognition. Its sentiment model analyzes text and returns a confidence score (0 to 1) and a sentiment label—positive, negative, or neutral—at both sentence and document levels, making it the correct choice for automatically assessing customer feedback.
- ✗
QnA Maker
Why it's wrong here
QnA Maker (also known as Custom Question Answering in Azure Language service) enables you to build a question-and-answer bot that matches user queries to answers from a knowledge base such as FAQs or support documents. It is designed to retrieve factual responses, not to infer the emotional tone or sentiment of an incoming message; using it for sentiment analysis would be a mismatch of purpose and produce no useful sentiment data.
Go deeper
Related to this question
Learn chapter
Machine Learning Core Concepts
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
Key term
Machine learning
Machine learning is a branch of artificial intelligence where computers learn patterns from data to make decisions or predictions without being explicitly programmed for every task.
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