Explanation:
HTTP Method: POST
Visual Feature: imageType
The question requires configuring an Azure AI Vision API request that determines if an image is clipart or a line drawing.
The Analyze Image endpoint (/analyze) of Azure AI Vision expects an HTTP POST request.
* GET is not valid for analysis with an image body.
* PATCH is irrelevant here.
* POST is correct because you are submitting image content or a URL for analysis.
Reference: Azure AI Vision Analyze Image API
Step 2 - Select the correct Visual FeatureThe visualFeatures query parameter determines what the API extracts.
description # Generates natural language description of the image.
tags # Identifies tags related to the image content.
objects # Detects objects and their locations.
imageType # Determines whether the image is a clipart, line drawing, or photo.
Since the requirement is to identify clipart vs line drawing, the correct choice is imageType.
Correct Request Completion:
Method: POST
Visual Feature: imageType
Microsoft ReferencesAnalyze Image (REST API) - Visual Features
Computer Vision API v3.2 Reference

You are working with a custom question answering project in Azure AI Language (formerly QnA Maker).
The requirement is to enable the chatbot to engage in multi-turn conversations.
* Multi-turn conversation: This occurs when a bot needs to ask clarifying questions or present follow-up options to guide the user toward the right answer.
Now let's evaluate the options:
* A. Add alternate questions
* Alternate questions help improve query matching by allowing different phrasings of the same question.
* This does not enable multi-turn dialogue.
* B. Enable chit-chat
* Chit-chat adds conversational personality (e.g., greetings, small talk).
* Useful for user engagement but not for structured multi-turn dialogues.
* C. Add follow-up prompts #
* Follow-up prompts allow you to define next-step questions after an answer.
* They are the key mechanism in custom question answering to enable multi-turn conversation flows.
* Example: If the answer is about "subscriptions," the follow-up prompts might include "How to upgrade?" or "How to cancel?"
* D. Enable active learning
* Active learning helps improve accuracy by suggesting alternative phrasing for questions based on user feedback.
* This is for model refinement, not multi-turn conversation.
Thus, the correct way to configure the project for multi-turn conversations is to add follow-up prompts.
The answer: C. Add follow-up prompts
* Custom question answering in Azure AI Language - Multi-turn conversations
* Custom question answering overview

Explanation:

Explanation:

Azure Cosmos DB supports multiple APIs, each aligned to a specific data model:
* Gremlin API
* Designed for graph data.
* Stores vertices (nodes) and edges (relationships).
* Query language: Gremlin.
* Correct mapping: Graph data.
* MongoDB API
* Designed for document data using JSON.
* Supports MongoDB wire protocol.
* Correct mapping: JSON documents.
* Table API
* Designed for key-value data.
* Compatible with Azure Table Storage.
* Correct mapping: Key/value data.
* Cassandra API
* Designed for wide-column (column-family) data.
* Uses CQL (Cassandra Query Language).
* Not listed in the answer area, but if included, it maps to columnar data, not the options shown here.
Correct Mapping:
* Graph data # Gremlin API
* JSON documents # MongoDB API
* Key/value data # Table API
* APIs in Azure Cosmos DB
* Choose the right API for Azure Cosmos DB

Explanation:
a tabular form of rows and columns
* Relational data is, by definition, data that adheres to the relational model.
* In the relational model, data is organized into tables, which consist of rows (records or tuples) and columns (fields or attributes). This is known as the tabular form.
* The other options are incorrect:
* Unstructured data is the opposite of relational data.
* A hierarchical folder structure is used for file organization, not the logical structure of relational data.
* Comma-separated value (CSV) files can contain relational data, but the core definition of relational data is the tabular structure, not the file format itself.