PassTIP는Microsoft인증DP-800시험에 대하여 가이드를 해줄 수 있는 사이트입니다. PassTIP는 여러분의 전업지식을 업그레이드시켜줄 수 잇고 또한 한번에Microsoft인증DP-800시험을 패스하도록 도와주는 사이트입니다. PassTIP제공하는 자료들은 모두 it업계전문가들이 자신의 지식과 끈임없은 경헌등으로 만들어낸 퍼펙트 자료들입니다. 품질은 정확도 모두 보장되는 문제집입니다.Microsoft인증DP-800시험은 여러분이 it지식을 한층 업할수 잇는 시험이며 우리 또한 일년무료 업데이트서비스를 제공합니다.
| 주제 | 소개 |
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| 주제 1 |
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| 주제 2 |
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| 주제 3 |
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거침없이 발전해나가는 IT업계에서 자신만의 자리를 동요하지 않고 단단히 지킬려면Microsoft인증 DP-800시험은 무조건 패스해야 합니다. 하지만Microsoft인증 DP-800시험패스는 하늘에 별따기 만큼 어렵습니다. 시험이 영어로 출제되어 공부자료 마련도 좀 힘든편입니다. 여러분들의 고민을 덜어드리기 위해PassTIP에서는Microsoft인증 DP-800시험의 영어버전 실제문제를 연구하여 실제시험에 대비한 영어버전Microsoft인증 DP-800덤프를 출시하였습니다.전문적인 시험대비자료이기에 다른 공부자료는 필요없이PassTIP에서 제공해드리는Microsoft인증 DP-800영어버전덤프만 공부하시면 자격증을 딸수 있습니다.
질문 # 47
Hotspot Question
You have a database named db1. The schema is stored in a Git repository as an SDK-style SQL database project. The repository contains the following GitHub Action workflow.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
정답：
설명：
질문 # 48
You have a database named DB1. The schema is stored in a Git repository as an SDK-style SQL database project.
You have a GitHub Actions workflow that already runs dotnet build and produces a database artifact.
You need to add a deployment step that publishes the dacpac file to an Azure SQL database by using the secrets stored in GitHub repository secrets What should you include in the workflow?
정답：C
설명：
The correct workflow step is Option C because it uses the Azure SQL GitHub Action to publish a .dacpac file and reads the connection string from GitHub repository secrets , which is exactly what the requirement asks for. Microsoft's Azure SQL GitHub Actions guidance shows using azure/sql-action@v2 with a connection string stored in secrets and a DACPAC path for deployment.
The key parts that make C correct are:
* uses: azure/sql-action@v2
* action: publish
* path: bin/Debug/db1.dacpac
* connection-string: ${{ secrets.SQL_CONNECTION_STRING }}
That matches the documented publish pattern for deploying a DACPAC to Azure SQL Database from GitHub Actions. Microsoft and the Azure SQL action documentation both describe Publish as the deployment action for applying a DACPAC to a target database, while Extract is used to create a DACPAC from an existing database, not deploy one.
Why the other options are incorrect:
* A uses an environment variable defined inline with a visible connection string rather than using GitHub repository secrets , which does not meet the requirement.
* B uses action: extract, which would create a DACPAC from a database instead of publishing the existing DACPAC artifact.
* D passes a target connection string to dotnet build, but the question says the workflow already runs dotnet build and produces a database artifact . The missing step is the deployment/publish step, not another build step. Microsoft's SQL project automation guidance separates build the DACPAC from publish the DACPAC .
질문 # 49
Vou have an Azure SQL database named SalesDB that contains a table named dbo. Articles, dbo.Articles contains two million articles with embeddmgs. The articles are updated frequently throughout the day.
You query the embeddings by using VECTOR_SEARQi
Users report that semantic search results do NOT reflect the updates until the following day.
Vou need to ensure that the embeddings are updated whenever the articles change. The solution must minimize CPU usage on SalesDB Which embedding maintenance method should you implement?
정답：D
설명：
The correct answer is B because the problem is not the vector search operator itself. The problem is that embeddings are becoming stale when article content changes . Microsoft documents that change data capture (CDC) tracks insert, update, and delete operations on source tables, which makes it the right mechanism to identify only the rows that changed.
This also best satisfies the requirement to minimize CPU usage on SalesDB . With CDC, the database only records the row changes, and the embedding regeneration work can be moved to an external process such as an Azure Functions app. That avoids running embedding generation inline inside the database for every update and avoids repeatedly recalculating embeddings for unchanged rows. In contrast, an hourly full-table regeneration would be extremely wasteful on a table with two million frequently updated articles, and a trigger that calls embedding generation per row would push expensive AI work into the transactional path of the database.
Option A is incorrect because changing from VECTOR_SEARCH to VECTOR_DISTANCE does not regenerate embeddings; it only changes the retrieval method. Microsoft states that VECTOR_SEARCH is the ANN search function, while VECTOR_DISTANCE performs exact distance calculation, so neither option addresses stale embedding data.
So the right design is:
* use CDC to detect only changed articles,
* process those changes outside the database,
* regenerate embeddings only for changed rows,
* write back the refreshed embeddings for current semantic search results.
질문 # 50
You have an Azure SQL database.
You need to create a scalar user-defined function (UDF) that returns the number of whole years between an input parameter named @OrderDate and the current date/time as a single positive integer. The function must be created in Azure SQL Database.
You write the following code.
What should you insert at line 05?
정답：B
설명：
Use RETURN to produce the scalar value of the function.
In an Azure SQL Database scalar function (a user-defined function that returns a single value), you must use the RETURN statement to return the scalar value.
The RETURN statement immediately terminates the function's execution and returns the value specified in its argument to the calling statement or procedure. The value returned must be of the data type specified in the RETURNS clause of the function definition.
The second argument to DATEDIFF should be @OrderDate as it is the start date, while the third argument is the end date, which is the current date.
Note:
DATEDIFF (Transact-SQL)
This function returns the count (as a signed integer value) of the specified datepart boundaries crossed between the specified startdate and enddate.
Syntax
DATEDIFF ( datepart , startdate , enddate )
Arguments
datepart
Specifies the units in which DATEDIFF reports the difference between the startdate and enddate.
Commonly used datepart units include month or second.
Reference:
https://learn.microsoft.com/en-us/sql/t-sql/functions/datediff-transact-sql
질문 # 51
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.
Hotspot Question
You need to create a solution that meets the development requirements for retrieving the patient transaction data. The solution must ensure that database developers use the resulting data to join to other tables.
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.
정답：
설명：
질문 # 52
......
Microsoft인증 DP-800시험은 빨리 패스해야 되는데 어디서부터 어떻게 시험준비를 시작해야 하는지 갈피를 잡을수 없는 분들은PassTIP가 도와드립니다. PassTIP의 Microsoft인증 DP-800덤프만 공부하면 시험패스에 자신이 생겨 불안한 상태에서 벗어날수 있습니다.덤프는 시장에서 가장 최신버전이기에 최신 시험문제의 모든 시험범위와 시험유형을 커버하여Microsoft인증 DP-800시험을 쉽게 패스하여 자격증을 취득하여 찬란한 미래에 더 가깝도록 도와드립니다.
DP-800시험패스 인증공부: https://www.passtip.net/DP-800-pass-exam.html