The answer is to configure indexers for SQL and SharePoint, and use the push API for the REST API, scheduling the indexers to run every 5 minutes. This approach is correct because Azure AI Search indexers natively support polling-based incremental indexing for structured sources like Azure SQL and SharePoint Online, while the push API allows you to programmatically ingest data from custom REST APIs without requiring a built-in connector. On the AI-102 exam, this scenario tests your understanding of hybrid indexing strategies—specifically, that indexers handle scheduled, change-tracking updates, whereas the push API is ideal for low-latency, custom data sources. A common trap is assuming a single indexer can pull from multiple heterogeneous sources, but each indexer binds to one data source type. Remember the memory tip: “Indexers for scheduled sources, push for custom APIs”—this helps you quickly match the tool to the source type when faced with multi-source indexing requirements.
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. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
You are designing an enterprise search solution using Azure AI Search. The solution must index data from multiple sources: SQL Database, SharePoint Online, and custom REST APIs. The search index must support faceted navigation and filtering by metadata such as department and document type. You also need to ensure that updates to source data are reflected in the index within 5 minutes. Which approach should you use?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure indexers for SQL and SharePoint, and use the push API for the REST API. Schedule indexers to run every 5 minutes.
Azure AI Search indexers can be scheduled to run periodically (e.g., every 5 minutes) and support various data sources including Azure SQL, SharePoint (via Graph API or custom indexer), and custom APIs via a custom indexer or push API. Using indexers for SQL and SharePoint, and a push API for the REST API, allows near-real-time updates. Option A is wrong because the push API alone for all sources would require custom code to poll sources. Option B is wrong because the push API for all sources is not efficient. Option D is wrong because a single indexer cannot index from multiple heterogeneous sources.
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 the push API to index all data from a custom application that polls all sources.
Why it's wrong here
Requires custom polling and does not leverage built-in indexers.
✗
Create a single indexer that reads from all three sources using a data source definition.
Why it's wrong here
An indexer can only have one data source.
✗
Use only indexers for all sources by creating a custom indexer for the REST API.
Why it's wrong here
Custom indexers are possible but not straightforward; push API is simpler.
✓
Configure indexers for SQL and SharePoint, and use the push API for the REST API. Schedule indexers to run every 5 minutes.
Why this is correct
Combines indexers for native sources and push API for custom data.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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: Configure indexers for SQL and SharePoint, and use the push API for the REST API. Schedule indexers to run every 5 minutes. — Azure AI Search indexers can be scheduled to run periodically (e.g., every 5 minutes) and support various data sources including Azure SQL, SharePoint (via Graph API or custom indexer), and custom APIs via a custom indexer or push API. Using indexers for SQL and SharePoint, and a push API for the REST API, allows near-real-time updates. Option A is wrong because the push API alone for all sources would require custom code to poll sources. Option B is wrong because the push API for all sources is not efficient. Option D is wrong because a single indexer cannot index from multiple heterogeneous sources.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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