AI-102 Plan and manage an Azure AI solution Practice Question
You are designing a solution that uses Azure AI Language to analyze customer feedback. The solution must detect sentiment, extract key phrases, and identify named entities. Which feature should you use?
⚠ Common exam trap
Many exam-takers confuse Azure AI Language with other Azure AI services that have overlapping names (e.g., Translator API for language tasks) or assume Speech or Vision services can perform text analysis, but only the Language service provides the specific trio of sentiment, key phrases, and NER.
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
✓
Azure AI Language service
The Azure AI Language service provides pre-built capabilities for sentiment analysis, key phrase extraction, and named entity recognition (NER) as part of its text analytics features. These three tasks are directly supported by the service's Analyze API, making it the correct choice for analyzing customer feedback text.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure AI Language service
Why this is correct
Azure AI Language consolidates sentiment analysis, key phrase extraction and named entity recognition within one resource, so a single call satisfies all three requirements without stitching separate services together. Its prebuilt models return sentiment scores, key phrases and entity categories directly, matching the stem's combined detection, extraction and identification constraints.
- ✗
Azure AI Speech service
Why it's wrong here
The Speech service handles speech-to-text, text-to-speech and translation of audio; it does not perform sentiment analysis, key phrase extraction or entity recognition on written feedback. It is tempting because it is an Azure AI Language-adjacent service, but it processes audio streams rather than analysing text.
- ✗
Azure AI Computer Vision
Why it's wrong here
Computer Vision analyses images and video for objects, OCR and spatial data; it cannot score sentiment or extract key phrases from feedback text. It is tempting because it is a Cognitive Service that returns structured insights, but its input modality is imagery, not the customer feedback text this solution must process.
- ✗
Translator API
Why it's wrong here
The Translator API performs text translation between languages and offers no sentiment scoring, key phrase extraction or named entity recognition. It is tempting because it belongs to Azure AI services and accepts text input, but the required three capabilities come from Azure AI Language's sentiment analysis, key phrase extraction and entity recognition features.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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