What is the main benefit of hybrid search that combines full-text and vector search?

It improves relevance by leveraging both keyword matching and semantic understanding

It guarantees exact matches for all queries

It eliminates the need for indexing

A research platform stores 10 million paper embeddings in Azure SQL Database. The team is evaluating search quality and notices that the top results for a query are not the most relevant. They suspect the vector index parameters are not optimal. Which evaluation approach would best help them diagnose and improve the index configuration?

Run a set of benchmark queries with known relevant results and measure recall@10 across different HNSW ef_search values.

Compare query latency before and after rebuilding the index with a larger number of lists.

Check the VECTORPROPERTY of the stored vectors to verify their dimensions are correct.

Run the same query multiple times and check if results are deterministic.

In Reciprocal Rank Fusion, what is the typical formula used to compute the fused score for a document?

Sum of 1/(k + rank) for each list where the document appears

Average of the raw scores from each list

Product of the ranks from each list

Microsoft Certified:SQL AI Developer Associate

Domain 3Objective 2

Design and Implement Intelligent Search DP-800 Practice Questions (Page 2)

Part of the Implement AI capabilities in database solutions domain, which accounts for 25–30% of the DP-800 exam. Microsoft does not publish an official question count, but from its 120-minute exam (~50–80 total, ~13–24 in this domain), expect 4–8 from this objective — we provide 47 practice questions to prepare you well beyond it. (estimate)

47questions here

10free pages

10concepts

25–30%of the exam

Questions 6–10

6foundation · easy
What is the main benefit of hybrid search that combines full-text and vector search?
Select an answer first
7expert · hard
A research platform stores 10 million paper embeddings in Azure SQL Database. The team is evaluating search quality and notices that the top results for a query are not the most relevant. They suspect the vector index parameters are not optimal. Which evaluation approach would best help them diagnose and improve the index configuration?
Select an answer first
8foundation · easy
Which data type is specifically designed to store vector embeddings in SQL Server 2025?
Select an answer first
9application · medium
A developer has a table with a VECTOR column containing embeddings that were generated by different models with different scales. They need to ensure that distance calculations are consistent across all vectors. Which function should they apply before computing distances?
Select an answer first
10foundation · easy
In Reciprocal Rank Fusion, what is the typical formula used to compute the fused score for a document?
Select an answer first

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Design and Implement Intelligent Search DP-800 Practice Questions (Page 2)

Questions 6–10

What is the main benefit of hybrid search that combines full-text and vector search?

Which data type is specifically designed to store vector embeddings in SQL Server 2025?

A developer has a table with a VECTOR column containing embeddings that were generated by different models with different scales. They need to ensure that distance calculations are consistent across all vectors. Which function should they apply before computing distances?

In Reciprocal Rank Fusion, what is the typical formula used to compute the fused score for a document?

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