AI-102 Plan and manage an Azure AI solution Practice Question
A company is designing a solution that uses Azure Cognitive Services for text analytics. The solution must meet the following requirements: - Detect sentiment in customer feedback. - Extract key phrases from the feedback. - Identify the language of the feedback automatically. - Ensure that the solution can scale to handle thousands of requests per second. Which TWO actions should the company take?
⚠ Common exam trap
Candidates often think language detection requires a separate dedicated service (Option A) or that the Free tier can scale (Option C), when in fact the Text Analytics API consolidates all required features and the Free tier is severely throttled for high-throughput workloads.
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
✓
Use the Text Analytics API for sentiment analysis and key phrase extraction.
The Text Analytics API (part of Azure Cognitive Services for Language) provides built-in capabilities for sentiment analysis, key phrase extraction, and language detection within a single API call. This eliminates the need for separate services and directly satisfies the requirements for detecting sentiment, extracting key phrases, and identifying language automatically.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy a separate Language Detection service for language identification.
Why it's wrong here
Text Analytics API includes language detection.
- ✓
Use the Text Analytics API for sentiment analysis and key phrase extraction.
Why this is correct
Text Analytics API provides these features.
- ✗
Use the Free pricing tier to reduce costs.
Why it's wrong here
Free tier has low throughput limits.
- ✓
Deploy the Cognitive Services resource in multiple regions and use a load balancer.
Why this is correct
Multi-region deployment with load balancing supports high throughput.
- ✗
Use Azure Functions to aggregate results from multiple API calls.
Why it's wrong here
Not required; the API handles results per request.
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