AI-102 Plan and manage an Azure AI solution Practice Question
Which THREE factors should you consider when selecting an Azure AI service for a solution that processes multilingual content?
⚠ Common exam trap
Test-takers frequently confuse cost or region considerations (Options D and E) with functional requirements for multilingual processing, overlooking that language support and custom model availability are the primary technical factors, while throughput limits (Option C) are also relevant for scaling but not language-specific.
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
✓
Availability of custom translation models.
Azure AI Translator and Azure AI Language support custom translation models via the Custom Translator feature, which allows you to build and deploy domain-specific translation models for multilingual content. This is critical when generic translation models fail to handle industry-specific terminology or brand voice, ensuring higher accuracy for specialized use cases like legal or medical documents.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Availability of custom translation models.
Why this is correct
Custom models improve translation accuracy for domain-specific terms.
- ✓
Supported languages for the service.
Why this is correct
The service must support the languages used in the content.
- ✓
Throughput limits and scaling options.
Why this is correct
Throughput affects how many requests can be processed.
- ✗
Geographic region of the resource.
Why it's wrong here
Region affects latency but is secondary to language support.
- ✗
Pricing per transaction.
Why it's wrong here
Pricing is important but not unique to multilingual processing.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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