- A
A Web API endpoint that processes documents
Custom skills are implemented as web APIs.
- B
Field mappings to pass data between the skill and the indexer
Mappings connect skill outputs to index fields.
- C
A machine learning model trained in Azure Machine Learning
Why wrong: Not required, but can be used inside the skill.
- D
An Azure Function to trigger the skill on a schedule
Why wrong: Skills are called during indexing, not scheduled.
- E
Input and output definitions in JSON format
Skills use JSON for context.
Question 892 of 993
Implement knowledge mining and information extraction solutions →hardMultiple SelectObjective-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.
Which THREE components are essential when building a custom skill for Azure AI Search?
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
✓
A Web API endpoint that processes documents
Option A is correct because a custom skill in Azure AI Search must be implemented as a Web API endpoint that integrates with the AI Search enrichment pipeline. This endpoint receives JSON payloads containing documents to be processed, performs custom logic (e.g., entity extraction, classification), and returns enriched JSON results. The Web API must be hosted (e.g., on Azure Functions, App Service) and conform to the specific request/response schema defined by Azure AI Search.
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.
- ✓
A Web API endpoint that processes documents
Why this is correct
Custom skills are implemented as web APIs.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Field mappings to pass data between the skill and the indexer
Why this is correct
Mappings connect skill outputs to index fields.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
A machine learning model trained in Azure Machine Learning
Why it's wrong here
Not required, but can be used inside the skill.
- ✗
An Azure Function to trigger the skill on a schedule
Why it's wrong here
Skills are called during indexing, not scheduled.
- ✓
Input and output definitions in JSON format
Why this is correct
Skills use JSON for context.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume a custom skill must involve a machine learning model (Option C) or a scheduled trigger (Option D), but the core requirement is simply a Web API endpoint with proper JSON input/output definitions and field mappings to integrate with the indexer.
Detailed technical explanation
How to think about this question
Under the hood, the custom skill Web API must handle HTTP POST requests with a JSON body containing a 'values' array, each element having a 'recordId' and 'data' object. The response must include a 'values' array with corresponding 'recordId', 'data', and optional 'errors'/'warnings'. Field mappings (Option B) are defined in the indexer to map skill outputs to index fields, while input/output definitions (Option E) are declared in the skill's JSON schema to specify parameter names and types. A real-world scenario: a custom skill that extracts product codes from PDFs using a regex library, deployed as an Azure Function, with field mappings sending the extracted codes to a 'productCode' index field.
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 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.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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: A Web API endpoint that processes documents — Option A is correct because a custom skill in Azure AI Search must be implemented as a Web API endpoint that integrates with the AI Search enrichment pipeline. This endpoint receives JSON payloads containing documents to be processed, performs custom logic (e.g., entity extraction, classification), and returns enriched JSON results. The Web API must be hosted (e.g., on Azure Functions, App Service) and conform to the specific request/response schema defined by Azure AI Search.
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.
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Last reviewed: Jul 4, 2026
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