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NEW QUESTION # 52
You need to enable similarity search to provide the analysts with the ability to retrieve the most relevant health summary reports. The solution must minimize latency.
What should you include in the solution?
Answer: D
Explanation:
The correct answer is D because the requirement is to enable similarity search over embedding vectors and to minimize latency . Microsoft documents that CREATE VECTOR INDEX is specifically used to create an index on vector data for approximate nearest neighbor (ANN) search , which is designed to accelerate vector similarity queries compared to exact k-nearest-neighbor scans.
This matches the scenario exactly. The VehicleHealthSummary table already includes an Embeddings (vector (1536)) column. In Microsoft SQL platforms, embeddings are stored in vector columns and queried for semantic similarity. To improve performance and reduce response time, Microsoft recommends a vector index , not a regular B-tree nonclustered index and not a full-text index. A vector index is purpose-built for finding the most similar vectors efficiently.
The other options are not appropriate:
* A would require manual comparison logic and would increase latency rather than minimize it.
* B is incorrect because a standard nonclustered index is not the index type used for vector similarity operations.
* C is incorrect because full-text indexes are for textual token-based search, not numeric vector embeddings.
Microsoft's current documentation is explicit that vector indexes support approximate nearest neighbor search , and that the optimizer can use the ANN index automatically for vector queries. That is the exam- aligned design choice when the goal is fast retrieval of the most relevant health summary reports from an embeddings column.
Topic 2, Fabrikam Case
- To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Existing Environment - Azure Environment - Fabrikam has a single Azure subscription in the East US 2 Azure region. The subscription contains an Azure SQL database named DB1. DB1 contains the following tables: * Patients * Employees * Procedures * Transactions * UsefulPrompts * ProcedureDocuments You store a column master key as a secret in Azure Key Vault. You have an on-premises application named TransactionProcessing that uses a hard-coded username and password in a connection string to access DB1.
Problem Statements - Users report that after executing a long-running stored procedure named sp_UpdateProcedureForPatient, updates to the underlying data are sometimes inconsistent. Requirements - Planned Changes - Fabrikam plans to manage all changes to Azure SQL Database objects by using source control in GitHub. Every pull request submitted to production will be validated before it can be merged.
Deployments must use the Release configuration. Security Requirements - Fabrikam identifies the following security requirements: * The TransactionProcessing application must use a passwordless connection to DB1. * The Employees table contains two columns named TaxID and Salary that must be encrypted at rest. * Auditors must have a tamper-evident history of transactions with cryptographic proof of changes to the employee data. Database Performance Requirements Records accessed by using sp_UpdateProcedureForPatient must NOT be changed by other transactions while the stored procedure runs.
AI Search, Embeddings, and Vector Indexing Fabrikam identifies the following AI-related requirements: * Queries to the ProcedureDocuments table must use Reciprocal Rank Fusion (RRF). * Users must be able to query the data in DB1 by using prompts in Copilot in Microsoft Fabric. * The UsefulPrompts table will store prompts that doctors can use to help diagnose patient illness by connecting to an Azure OpenAI endpoint.
Development Requirements - Fabrikam identifies the following development requirements: * Provide the functionality to retrieve all the transactions of a given patient between two dates, showing a running total. * Expose a Data API builder (DAB) configuration file to enable Azure services to perform the following operations over a REST API: o Read data from the procedures table without authentication. o Read and insert data into the Transactions table once authenticated. o Execute the sp_UpdateProcedurePatient stored procedure. * Provide the functionality to retrieve a list of the names of patients who underwent medical procedures during the last 30 days. * Information for each medical procedure will be stored in a table. The table will be used with a large language model (LLM) for user querying and will have the following structure.
DAB
You create a DAB configuration file that meets the development requirements for DB1 and includes the following entities.
NEW QUESTION # 53
You have a SQL database in Microsoft Fabric named Sales BD that contains a table named dbo.Products. You need to modify SalesBD to meet the following requirements:
* Create a vector index on the appropriate column.
* Use a supplied natural language query vector.
How should you complete the Transact-SQL code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The first correct selection is embedding because a vector index must be created on the vector column , not on a scalar distance column or a text column such as product_name. Microsoft's CREATE VECTOR INDEX documentation shows that the index is created directly on the vector-valued column, for example ON product_embeddings(embedding).
The second correct selection is VECTOR_SEARCH because the requirement is to use a supplied natural language query vector and search against the indexed embeddings. Microsoft documents that VECTOR_SEARCH is the Transact-SQL function for approximate nearest neighbor vector retrieval and that it applies to SQL database in Microsoft Fabric as well as other supported SQL platforms.
This also matches the shown code pattern:
* declare a vector variable such as @query_vector VECTOR(1536),
* create a vector index on dbo.Products(embedding),
* query with VECTOR_SEARCH(... SIMILAR_TO = @query_vector, METRIC = ' cosine ' , TOP_N =
10).
NEW QUESTION # 54
You have a Microsoft SQL Servei 2025 database that contains a table named dbo.Customer-Messages, dbo.
Customer-Messages contains two columns named HessagelD (int) and MessageRaw (nvarchar(iux)).
MessageRaw can contain a phone number in multiple formats. and some rows do NOT contain a phone number. You need to write a single SELECT query that meets the following requirements:
* The query must return Message ID, RawNumber. DigitsOnly, and PhoneStatus.
* RawNumber must contain the first substring that matches a phone-number pattern, or NULL if no match exists.
* DigitsOnly must remove all non-digit characters from RawNumber. or return NULL.
* PhoneStatus must return Valid when a phone number exists in MessageRaw. otherwise return Missing.
How should you complete the Transact-SQL query? lo answer, drag the appropriate values To the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The correct drag-and-drop mapping is based on the documented behavior of the new SQL regular expression functions.
For RawNumber , the requirement is to return the first substring in MessageRaw that matches the phone- number pattern, or NULL if nothing matches. That is exactly what REGEXP_SUBSTR does: it extracts the matched substring from the source text. Microsoft documents REGEXP_SUBSTR as the function that
"extracts parts of a string based on a regular expression pattern" and returns the matched occurrence.
For DigitsOnly , you first need the matched phone substring, then remove all non-digit characters from it. The correct combined expression is REGEXP_REPLACE( REGEXP_SUBSTR( so the matched substring is passed into REGEXP_REPLACE, which strips characters matching \D. Microsoft documents REGEXP_REPLACE as returning a modified source string with matching patterns replaced. Using it around REGEXP_SUBSTR satisfies the "digits only or NULL" requirement in one select expression.
For PhoneStatus , the requirement is simply to return Valid when a phone number exists and Missing otherwise. That is a Boolean test, so REGEXP_LIKE is the right function. Microsoft documents REGEXP_LIKE as returning a Boolean value indicating whether the input matches the regex pattern.
NEW QUESTION # 55
Case Study 2 - Fabrikam
Existing Environment
Azure Environment
Fabrikam has a single Azure subscription in the East US 2 Azure region. The subscription contains an Azure SQL database named DB1. DB1 contains the following tables:
* Patients
* Employees
* Procedures
* Transactions
* UsefulPrompts
* ProcedureDocuments
You store a column master key as a secret in Azure Key Vault.
You have an on-premises application named TransactionProcessing that uses a hard-coded username and password in a connection string to access DB1.
Problem Statements
Users report that after executing a long-running stored procedure named sp_UpdateProcedureForPatient, updates to the underlying data are sometimes inconsistent.
Requirements
Planned Changes
Fabrikam plans to manage all changes to Azure SQL Database objects by using source control in GitHub. Every pull request submitted to production will be validated before it can be merged.
Deployments must use the Release configuration.
Security Requirements
Fabrikam identifies the following security requirements:
* The TransactionProcessing application must use a passwordless connection to DB1.
* The Employees table contains two columns named TaxID and Salary that must be encrypted at rest.
* Auditors must have a tamper-evident history of transactions with cryptographic proof of changes to the employee data.
Database Performance Requirements
Records accessed by using sp_UpdateProcedureForPatient must NOT be changed by other transactions while the stored procedure runs.
AI Search, Embeddings, and Vector Indexing
Fabrikam identifies the following AI-related requirements:
* Queries to the ProcedureDocuments table must use Reciprocal Rank Fusion (RRF).
* Users must be able to query the data in DB1 by using prompts in Copilot in Microsoft Fabric.
* The UsefulPrompts table will store prompts that doctors can use to help diagnose patient illness by connecting to an Azure OpenAI endpoint.
Development Requirements
Fabrikam identifies the following development requirements:
* Provide the functionality to retrieve all the transactions of a given patient between two dates, showing a running total.
* Expose a Data API builder (DAB) configuration file to enable Azure services to perform the following operations over a REST API:
- Read data from the procedures table without authentication.
- Read and insert data into the Transactions table once authenticated.
- Execute the sp_UpdateProcedurePatient stored procedure.
* Provide the functionality to retrieve a list of the names of patients who underwent medical procedures during the last 30 days.
* Information for each medical procedure will be stored in a table. The table will be used with a large language model (LLM) for user querying and will have the following structure.
DAB
You create a DAB configuration file that meets the development requirements for DB1 and includes the following entities.
You implement ProcedureDocuments to support the planned changes.
When users consume data through the Retrieval Augmented Generation (RAG) pattern, they experience data retrieval delays.
You need to improve the data retrieval performance and reduce the number of tokens per retrieval.
What should you implement?
Answer: D
Explanation:
Scenario: Fabrikam identifies the following AI-related requirements: Queries to the ProcedureDocuments table must use Reciprocal Rank Fusion (RRF).
To remedy data retrieval delays in a Retrieval Augmented Generation (RAG) pattern using Reciprocal Rank Fusion (RRF) on an Azure SQL Database table, you should use embeddings.
In a RAG architecture, retrieval delays often stem from inefficient or computationally heavy search processes. While RRF is excellent for merging results from multiple sources (like combining keyword and vector searches), the core of the speed problem typically lies in how the initial data is indexed and retrieved.
Role of Embeddings
Vector Search Acceleration: Embeddings convert text into high-dimensional vectors. Azure SQL Database can perform similarity searches on these vectors much faster than complex semantic text matching.
Hybrid Search Synergy: RRF is most effective when it fuses results from a keyword search (fast) and a vector search (powered by embeddings). Using embeddings ensures that the "semantic" side of the retrieval is streamlined.
Pre-computation: Since embeddings are generated once during ingestion, the retrieval phase only requires a distance calculation (e.g., Cosine Similarity), which is significantly faster than real- time natural language parsing during each query.
Reference:
https://pratikbarjatya.medium.com/unlocking-the-power-of-language-with-retrieval-augmented- generation-rag-14123cc275e6
NEW QUESTION # 56
You have an Azure SQL database named SalesDB that supports an AI-enabled product search application.
SalesDB has a table named SalesLT.Product that contains the following columns:
* ProductID (int)
* Name (nvarchar(100))
* ListPrice (decimal(18,2))
You need to create an object that returns products priced above a caller-provided threshold. The solution must meet the following requirements:
* Support being used in a join.
* Accept one input parameter.
* Return a table result.
Answer:
Explanation:
Explanation:
NEW QUESTION # 57
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