AI-200 Data Management Services And Vector Search Practice Test 4 — 15 Questions

Question 1

Which Azure AI Search API parameter allows you to specify a vector query alongside traditional keyword search terms when executing a hybrid search?

Accepted Answer

vectorQueries. In Azure AI Search queries, the vectorQueries parameter is used to pass vector embedding query objects during search requests.

Answer

embeddingQuery

Answer

knnQuery

Answer

vectorSearchParam

Question 2

When configuring an Azure AI Search vectorizer for integrated vectorization, which TWO parameters or connections must be specified to link to an Azure OpenAI deployment? (Choose two)

Accepted Answer

Model name (e.g., text-embedding-ada-002). Integrated vectorization requires configuring the model name (e.g., text-embedding-ada-002) and the resource URL/authentication details of the Azure OpenAI service.

Answer

SQL Server connection string

Answer

Cosmos DB container database name

Answer

Blob storage SAS token expiration time

Question 3

You are designing a data layer architecture for an enterprise AI assistant that requires high-performance vector search, structured filtering, and multi-tenant isolation. Which THREE design patterns should you consider? (Choose three)

Accepted Answer

Combining vector similarity with metadata filters to narrow search scope. Effective AI data layer design patterns include logical partitioning for multi-tenancy, pre-filtering metadata, and hybrid retrieval combining keyword and vector search.

Answer

Storing all tenant data in a single unindexed JSON blob without partition keys

Answer

Hardcoding all user prompts directly into the search index schema

Question 4

You are writing a query in Azure Cosmos DB for NoSQL that sorts results by vector similarity and also filters results by a category property. How must you order the clauses in your SQL statement?

Accepted Answer

The WHERE clause must come before the ORDER BY VectorDistance() clause. In Azure Cosmos DB, when using VectorDistance in an ORDER BY clause along with a WHERE filter, the WHERE clause must precede the ORDER BY clause.

Answer

VectorDistance must be placed in the SELECT clause instead of ORDER BY

Answer

WHERE and ORDER BY clauses cannot be used in the same query when using vectors

Answer

The ORDER BY clause must come before the WHERE clause

Question 5

Which REST API HTTP method is used to create or update an index definition in Azure AI Search?

Accepted Answer

PUT. Azure AI Search REST API uses HTTP PUT to create or fully update an index definition.

Answer

GET

Answer

PATCH

Answer

DELETE

Question 6

Which tool in Azure Portal allows you to test search queries, inspect index schemas, and view JSON responses for Azure AI Search?

Accepted Answer

Search explorer. The Search Explorer in the Azure Portal provides a built-in UI interface for testing queries and inspecting indices in Azure AI Search.

Answer

Metrics Advisor

Answer

Data Explorer

Answer

Log Analytics

Question 7

You are migrating a large vector dataset into an Azure AI Search index. To maximize ingestion speed and throughput, you temporarily adjust index settings. Which index configuration property should you modify during bulk ingestion?

Accepted Answer

Scale out search units (replicas and partitions) to distribute ingestion load. During heavy bulk ingestion, increasing the replica and partition count or adjusting merge/indexing batch sizes improves speed, but specifically, scaling out search units or temporarily disabling semantic ranker overhead optimizes throughput.

Answer

Set HNSW efConstruction to 10,000 to maximize graph build precision

Answer

Disable all scoring profiles and set vector dimensions to 1

Answer

Switch the index tier from Standard to Free

Question 8

When configuring vector search in Azure AI Search, which TWO components are defined within the vectorSearch object of an index definition? (Choose two)

Accepted Answer

algorithms. The vectorSearch object in Azure AI Search contains algorithm configurations and vector profiles.

Answer

sqlPartitionKey

Answer

storageAccountConnectionString

Answer

cosmosContainerName

Question 9

You are troubleshooting a scenario where hybrid queries in Azure AI Search are returning unexpected relevance rankings. Which THREE factors could influence the final score when using hybrid search with semantic ranking? (Choose three)

Accepted Answer

Semantic ranker deep learning re-scoring. Hybrid search scores are influenced by BM25 full-text scores, vector similarity scores, RRF normalization, and semantic ranker re-scoring.

Answer

Virtual machine CPU core count assigned to the client application

Answer

Azure Blob Storage container access tier (Hot vs Cool)

Question 10

When designing an Azure AI Search index schema, which TWO properties must be defined for every field in the index? (Choose two)

Accepted Answer

name. Every field in an Azure AI Search index definition must have a name and a type (Edm data type).

Answer

analyzerName

Answer

scoringProfile

Answer

vectorDimensions

Question 11

You are designing an application that stores vector embeddings in Azure Cosmos DB for NoSQL. You want to ensure that vectors are stored securely and that all data at rest is encrypted using customer-managed keys (CMK). How is this achieved in Cosmos DB?

Accepted Answer

Configure customer-managed keys (CMK) at the Azure Cosmos DB account level referencing Azure Key Vault. Customer-managed keys in Azure Cosmos DB are configured at the Azure Cosmos DB account level using Azure Key Vault integration.

Answer

Enable encryption inside the vector embedding policy JSON definition

Answer

Encrypt each individual vector array in client application code before inserting

Answer

Store vectors in Azure Blob Storage with a CMK policy

Question 12

You are building an AI search solution in Azure AI Search. You need to ensure that when documents are deleted from the primary database, they are also automatically removed from the search index without requiring manual API calls. How should you configure the indexer?

Accepted Answer

Configure a soft-delete policy on the indexer referencing a deletion tracking column or flag in the data source. Azure AI Search indexers support change detection and soft-delete policies (such as Soft Delete Column) to automatically reflect deletions in the search index.

Answer

Write a custom Azure Function triggered by every delete event to issue an HTTP DELETE to the search index

Answer

Re-create the entire search index from scratch daily

Answer

Set the index retention policy to auto-purge every 24 hours

Question 13

You are configuring semantic ranking in Azure AI Search. You need to specify which fields in your index contain the title and content that the semantic ranker should analyze. Where do you configure these field mappings?

Accepted Answer

In the semantic configuration section of the index schema. Semantic configuration in Azure AI Search defines the prioritized fields for title, content, and keywords used by the semantic ranker.

Answer

In the indexer skill set cognitive map

Answer

In the Azure OpenAI model deployment properties

Answer

In the vector profile definition

Question 14

Which distance metric in Azure Cosmos DB vector search calculates the inner product of two vectors, measuring both magnitude and angle?

Accepted Answer

dotproduct. The dotproduct distance metric computes the inner product of two vectors.

Answer

cosine

Answer

euclidean

Answer

manhattan

Question 15

You are optimizing an enterprise Azure Cosmos DB for NoSQL vector database. Which THREE administrative or architectural practices help ensure high availability and predictable performance? (Choose three)

Accepted Answer

Choose a partition key that evenly distributes data and query load across physical partitions. Ensuring high performance and availability in Cosmos DB involves configuring consistent request unit provisioning, setting up multi-region writes, and defining effective partition keys.

Answer

Store all documents in a single partition without a partition key

Answer

Disable automatic indexing entirely across all properties