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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI-Enabled Database Solutions |
| Exam Number: | DP-800 |
| Available Languages: | English, Chinese (Traditional), French, Arabic (Saudi Arabia), Chinese (Simplified), Indonesian (Indonesia), German, Japanese, Spanish, Korean, Portuguese (Brazil), Italian |
| Related Certifications: | Microsoft Certified: SQL AI Developer Associate |
| Exam Price: | $165 USD |
| Exam Duration: | 100 minutes |
| Certificate Validity Period: | 1 year |
| Passing Score: | 700 |
| Exam Format: | Build list, Drag and drop, Multiple choice, Case studies, Multiple select |
| Real Exam Qty: | 40-60 |
| Sample Questions: | Microsoft DP-800 Sample Questions |
| Exam Way: | Online proctored or in-person at a testing center |
| Pre Condition: | No specific prerequisites, but candidates should have experience with SQL and a basic understanding of Azure services. Familiarity with AI or machine learning concepts is recommended. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/dp-800/ |
最も短い時間で自分のIT技能を増強したいけれど、質の良い学習教材がないので悩んでいますか。ご心配なく、JapancertのMicrosoftのDP-800試験トレーニング資料を手に入れるなら、ITに関する認定試験はなんでも楽に合格できます。Japancertの MicrosoftのDP-800試験トレーニング資料は高度に認証されたIT領域の専門家の経験と創造を含めているものです。Japancertは君にとって、ベストな選択だといっても良いです。
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
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| トピック 2 |
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| トピック 3 |
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質問 # 32
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?
正解：A
解説：
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 .
質問 # 33
You need to create a solution that meets the development requirements for retrieving the patient lists.
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.
正解：
解説：
Explanation:
where exists 2. where p.PatientID = pr.PatientID Otherwise we filter PatientID twice. Having in the subquery does not work without group by and the date filter does not work without where.
質問 # 34
You have a SQL database in Microsoft Fabric that contains a nvarchar (max) column named MessageText. An ID is always contained within the first paragraph of MessageText.
You need to write a Transact-SQL query that uses REGEXP_SUBSTR to extract the ID from MessageText.
What should you include in the query?
正解：D
解説：
To extract an ID (e.g., alphanumeric) from the first paragraph of an nvarchar(max) column in Microsoft Fabric using STRING_ESCAPE, use STRING_SPLIT or CHARINDEX to isolate the first paragraph, apply STRING_ESCAPE, and a regex pattern.
Note: T-SQL does not natively support a REGEXP_SUBSTR function like Oracle/Snowflake. The solution below uses STRING_ESCAPE followed by pattern matching via PATINDEX and SUBSTRING to extract a typical alphanumeric ID.
Reference:
https://learn.microsoft.com/en-us/sql/t-sql/queries/contains-transact-sql
質問 # 35
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?
正解：C
解説：
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.
質問 # 36
You have a Microsoft SQL Server 2025 instance that contains a database named SalesDB SalesDB supports a Retrieval Augmented Generation (RAG) pattern for internal support tickets. The SQL Server instance runs without any outbound network connectivity.
You plan to generate embeddings inside the SQL Server instance and store them in a table for vector similarity queries.
You need to ensure that only a database user account named AlApplicationUser can run embedding generation by using the model.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
正解：B、C
解説：
Because the SQL Server 2025 instance has no outbound network connectivity , the embedding model cannot rely on a remote REST endpoint such as Azure AI Foundry or Azure OpenAI. Microsoft's CREATE EXTERNAL MODEL documentation includes a local deployment pattern using ONNX Runtime running locally with local runtime/model paths . That is the right design when embeddings must be generated inside the SQL Server instance without external network access. Microsoft explicitly documents a local ONNX Runtime example for SQL Server 2025 and notes the required local runtime setup and model path configuration.
The permission requirement is handled by granting the application user access to use the external embeddings model. Microsoft's AI_GENERATE_EMBEDDINGS documentation states that, as a prerequisite, you must create an external model of type EMBEDDINGS that is accessible via the correct grants, roles, and/or permissions . Among the choices, the exam-appropriate action is to grant execute permission on the external model project to AlApplicationUser so only that database user can run embedding generation through the model.
質問 # 37
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