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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI-Enabled Database Solutions |
| Exam Number: | DP-800 |
| Certificate Validity Period: | 1 year |
| Passing Score: | 700 |
| Exam Format: | Multiple select, Case studies, Multiple choice, Build list, Drag and drop |
| Real Exam Qty: | 40-60 |
| Available Languages: | Portuguese (Brazil), Spanish, Chinese (Simplified), Korean, Arabic (Saudi Arabia), Japanese, Chinese (Traditional), French, German, Indonesian (Indonesia), English, Italian |
| Exam Duration: | 100 minutes |
| Exam Price: | $165 USD |
| Related Certifications: | Microsoft Certified: SQL AI Developer Associate |
| 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/ |
Achieving the Developing AI-Enabled Database Solutions (DP-800) certification can significantly impact your career progression and earning potential. This certification showcases your expertise and knowledge to employers, making you a valuable asset in the Microsoft DP-800 industry. With the rapidly evolving nature of the Microsoft world, staying up-to-date with the latest technologies and trends is crucial. The DP-800 Certification Exam enables you to learn these changes and ensures you remain current in your field.
| Topic | Details |
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| Topic 1 |
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| Topic 2 |
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| Topic 3 |
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NEW QUESTION # 46
You are developing an Azure SQL database solution from a locally cloned GitHub repository by using Microsoft Visual Studio Code and GitHub Copilot Chat.
You need to ensure that GitHub Copilot Chat can call the hosted GitHub MCP Server tools by using OAuth.
The MCP server configuration must be scoped to the repository.
What should you do in Visual Studio Code?
Answer: C
NEW QUESTION # 47
You have an Azure SQL database named SalesDB that contains a table named dbo.Articles.
dbo.Articles contains two million articles with embeddings. The articles are updated frequently throughout the day.
You query the embeddings by using VECTOR_SEARCH.
Users report that semantic search results do NOT reflect the updates until the following day.
You 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?
Answer: D
Explanation:
This setup is a solid way to bridge the gap between your SQL updates and your vector index. By using CDC (Change Data Capture), you avoid the heavy lifting of scanning the entire table for changes, which keeps your database CPU overhead low.
To make this work efficiently within the Azure Functions app, you'll typically want to:
Batch the updates: Instead of triggering a function for every single row change, process small batches of CDC records to reduce the number of calls to your embedding model (like OpenAI).
Use an Upsert logic: In your function, ensure the code handles both new inserts and updates by overwriting the existing embedding for a specific Article ID in the database.
Implement a "Cool-down" or Timer: If the "frequent updates" happen in bursts, you can use an Azure Service Bus or Storage Queue between the CDC process and the Function to smooth out the processing load.
Reference:
https://fivetran.com/docs/connectors/databases/troubleshooting/log-based-cdc-impact
NEW QUESTION # 48
You need to recommend a solution for the development team to retrieve the live metadata. The solution must meet the development requirements.
What should you include in the recommendation?
Answer: D
Explanation:
The best recommendation is to use an MCP server. In the official DP-800 study guide, Microsoft explicitly lists skills such as configuring Model Context Protocol (MCP) tool options in a GitHub Copilot session and connecting to MCP server endpoints, including Microsoft SQL Server and Fabric Lakehouse. That makes MCP the exam-aligned mechanism for enabling AI-assisted tools to work with live database context rather than static snapshots.
This also matches the stated development requirement: the team will use Visual Studio Code and GitHub Copilot and needs to retrieve live metadata from the databases. Microsoft's documentation for GitHub Copilot with the MSSQL extension explains that Copilot works with an active database connection, provides schema- aware suggestions, supports chatting with a connected database, and adapts responses based on the current database context. Microsoft also documents MCP as the standard way for AI tools to connect to external systems and data sources through discoverable tools and endpoints.
The other options do not satisfy the "live metadata" requirement as well:
A .dacpac is a point-in-time schema artifact, not live metadata.
A Copilot instruction file provides guidance, not live database discovery.
Including the database project in the repository helps source control and deployment, but it still does not provide live database metadata by itself.
Topic 2, Fabrikam Case
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 # 49
You have an Azure SQL database that contains a table named Rooms. Roomswas created by using the following Transact-SQL statement.
You discover that some records in the Rooms table contain NULL values for the Owner field.
You need to ensure that all future records have a value for the Owner field.
What should you add?
Answer: D
Explanation:
A CHECK constraint is one way to do it.
If you use a CHECK constraint (e.g., CHECK (ColumnName IS NOT NULL)), the database will indeed reject new NULL entries. However, the column's metadata will still technically allow NULLs, which can sometimes affect how external tools or APIs interact with your schema.
Reference:
https://www.postgresql.org/docs/7.0/sql-createtable.htm
NEW QUESTION # 50
You have an Azure SQL database that contains a table named Customer. Customer contains the following columns:
- NationalIDNumber is unique per customer.
- InvestigationNotes contains free-form text.
You have a stored procedure that performs point lookups by NationalIDNumber and returns InvestigationNotes in the query results without filtering on InvestigationNotes.
You need to encrypt both columns by using Always Encrypted and the highest security possible.
Which type of Always Encrypted encryption should you use for each column?
Answer: A
Explanation:
To achieve the highest security for an Azure SQL Database using Always Encrypted, you must use Randomized Encryption for the InvestigationNotes and Deterministic Encryption for the NationalIDNumber.
While "Randomized" is more secure, it does not support point lookups (equality searches).
Therefore, a hybrid approach is required to maintain functionality while maximizing protection.
Recommended Encryption Settings
* NationalIDNumber
Deterministic is required to allow the Stored Procedure to perform point lookups (WHERE NationalIDNumber = @id).
* InvestigationNotes
Use randomized as it provides the highest security. It prevents pattern matching and "leakage" for sensitive text.
Reference:
https://medium.com/@ih_hira/implementing-always-encrypted-with-azure-key-vault-and-entity- framework-core-in-azure-sql-part-1-3a0e5fd7ed9b
NEW QUESTION # 51
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