- A
Use separate skillsets for each tenant
Why wrong: Skillsets do not provide data isolation.
- B
Create a separate search service for each tenant
Why wrong: Expensive and hard to manage.
- C
Use a single index with a tenant ID field and filter queries by that field
Index-level security with filters is the recommended approach.
- D
Use separate data sources within the same index
Why wrong: Data sources do not enforce tenant isolation.
Question 490 of 993
Implement knowledge mining and information extraction solutions →hardMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
This AI-102 practice question tests your understanding of implement knowledge mining and information extraction solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Your knowledge mining solution ingests documents from multiple tenants. Each tenant's data must be isolated and searchable only by that tenant. You have a single Azure AI Search service. How should you implement multi-tenancy?
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 a single index with a tenant ID field and filter queries by that field
Option C is correct because Azure AI Search supports multi-tenancy within a single service by using a shared index with a tenant ID field. Each document is tagged with a tenant identifier, and queries are scoped using OData `$filter` expressions (e.g., `$filter=tenantId eq 'tenant123'`). This ensures data isolation while keeping costs low and management simple, as only one search service and one index are needed.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use separate skillsets for each tenant
Why it's wrong here
Skillsets do not provide data isolation.
- ✗
Create a separate search service for each tenant
Why it's wrong here
Expensive and hard to manage.
- ✓
Use a single index with a tenant ID field and filter queries by that field
Why this is correct
Index-level security with filters is the recommended approach.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use separate data sources within the same index
Why it's wrong here
Data sources do not enforce tenant isolation.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse data sources (which are just ingestion pipelines) with data partitioning, leading them to think separate data sources or skillsets provide isolation, when in fact only query-time filtering or separate indexes enforce tenant boundaries.
Detailed technical explanation
How to think about this question
Under the hood, Azure AI Search uses inverted indexes that are shared across all documents in an index. The tenant ID field is indexed as a filterable attribute, and the `$filter` clause is applied at query time to restrict results. For stronger isolation, you can also use index-level security via search filters or implement a custom security trimming solution using Azure AD tokens. In high-scale scenarios, you might combine this with index sharding or separate indexes per tenant if query performance becomes a concern.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement knowledge mining and information extraction solutions — This question tests Implement knowledge mining and information extraction solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a single index with a tenant ID field and filter queries by that field — Option C is correct because Azure AI Search supports multi-tenancy within a single service by using a shared index with a tenant ID field. Each document is tagged with a tenant identifier, and queries are scoped using OData `$filter` expressions (e.g., `$filter=tenantId eq 'tenant123'`). This ensures data isolation while keeping costs low and management simple, as only one search service and one index are needed.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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