Microsoft SQL AI Developer (DP-800) Exam Questions 2026
Microsoft SQL AI Developer (DP-800) Exam Questions 2026
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Question 1:
You need a reusable object that calculates a discount percentage and returns just one numeric result to the calling query. Which object fits best?
A.INSTEAD OF trigger
B.View
C.Scalar function
D.Stored procedure
Answer: C
Explanation:
Correct
C. Scalar function: This is the correct answer. A scalar function in SQL Server is specifically designed to accept parameters, perform a calculation, and return a single, atomic value (in this case, a numeric discount percentage). Because it returns a single value, it can be called directly within a SELECT statement (e.g., SELECT ProductID, dbo.GetDiscount(Price) FROM Products), making it the ideal choice for row-by-row calculations in a query.
Incorrect:
A. INSTEAD OF trigger: Incorrect. An INSTEAD OF trigger is a stored program that executes in place of a data modification operation (INSERT, UPDATE, or DELETE). Its purpose is to handle complex validation or logical branching during data modification, not to perform calculations to be consumed by a query. It cannot return a value to a calling query in the manner requested.
B. View: Incorrect. A view is a virtual table based on the result-set of a SQL statement. While views are reusable, they are designed to return sets of data (rows and columns), not to perform specialized scalar calculations that are then invoked by a specific query as a function call.
D. Stored procedure: Incorrect. While a stored procedure can calculate values and return them via an output parameter, it cannot be called directly within a SELECT statement’s column list. To get a value from a stored procedure, you must use an EXEC command, usually requiring the use of a temporary table or table variable to capture the result, which makes it unsuitable for the requirement of a simple, reusable calculation embedded in a query.
Question 2:
Which function should you use when you need a normalized version of a vector before comparison?
A.REGEXP_LIKE
B.VECTOR_DISTANCE
C.VECTORPROPERTY
D.VECTOR_NORMALIZE
Answer: D
Explanation:
D. VECTOR_NORMALIZE: This is the correct answer. In SQL-based AI development, normalization is a critical preprocessing step for vector data. It scales the vector to have a unit length (often referred to as L2 normalization). Normalizing vectors before performing similarity comparisons (like cosine similarity) ensures that the distance metric focuses on the direction of the vectors rather than their magnitude, which is standard practice for semantic search and retrieval-augmented generation (RAG) pipelines.
Incorrect:
A. REGEXP_LIKE: Incorrect. This is a pattern-matching function used for regular expressions in string data. It has no application in vector math or data preprocessing for AI models.
B. VECTOR_DISTANCE: Incorrect. While this is a critical vector function, its purpose is to calculate the distance or similarity between two vectors (e.g., Euclidean or Cosine distance), not to perform the normalization of a single vector.
C. VECTORPROPERTY: Incorrect. This function is typically used to retrieve specific metadata or properties about a vector, such as its dimensions or data type, rather than performing mathematical operations like normalization.
Question 3:
API telemetry such as request rate, failures, and traces should be captured for the SQL-backed API service. Which Azure service is the best fit?
A.Application Insights
B.Change Tracking
C.Log Analytics
D.SEQUENCE
Answer: A
Explanation:
Correct
A. Application Insights: This is the correct answer. Application Insights is an Application Performance Management (APM) service specifically designed to monitor live applications. It excels at collecting and visualizing the exact metrics you described: request rates, failure rates, and distributed traces. It integrates directly with Azure-hosted services to provide detailed diagnostics and performance dashboards, making it the industry standard for monitoring the health and performance of API services in an Azure environment.
Incorrect:
B. Change Tracking: Incorrect. Change Tracking is a SQL Server database feature used to capture information about which rows in a table were changed (inserted, updated, or deleted). It is a database-level synchronization mechanism, not a telemetry tool for monitoring API performance or request metrics.
C. Log Analytics: Incorrect. While Log Analytics is a powerful tool for storing and querying logs (and Application Insights can store its data in a Log Analytics workspace), it is a storage and analysis platform rather than the primary telemetry collection service for application-level metrics. You use Application Insights to instrument the API and generate the metrics; Log Analytics is the underlying repository used for advanced, long-term log storage.
D. SEQUENCE: Incorrect. A SEQUENCE is a user-defined schema-bound object in SQL Server that generates a sequence of numeric values based on a defined specification. It is a database-level utility for generating unique IDs and has no relationship to API monitoring or telemetry.
Question 4:
An Azure-hosted application needs to connect to Azure SQL without storing usernames or passwords in configuration files. Which approach is best?
A. SQL authentication
B.Service principal secret
C.Managed Identity
D.Password in connection string
Answer: C
Explanation:
C. Managed Identity: This is the correct answer. Managed Identity provides an identity for your application in Microsoft Entra ID (formerly Azure AD). This allows your application to authenticate to Azure SQL Database without needing to store any credentials (like usernames or passwords) in your code or configuration files. When the application runs, it uses its assigned identity to request an access token from the platform, which is then used to securely connect to the database.
Incorrect:
A. SQL authentication: Incorrect. SQL authentication relies on a username and password defined within the database itself. Using this method requires you to manage and store these credentials (often in configuration files or key vaults), which increases security risks compared to the token-based authentication provided by Managed Identity.
B. Service principal secret: Incorrect. While a Service Principal can be used to authenticate, it requires you to manage a "client secret." This secret must be stored somewhere (like Azure Key Vault), and if not handled correctly, it can be leaked or rotated improperly. Managed Identity is superior because it is handled automatically by the Azure platform, eliminating the need for secret management entirely.
D. Password in connection string: Incorrect. This is a severe security vulnerability. Hardcoding credentials in connection strings is against all security best practices. It exposes sensitive access information to anyone with access to the source code, deployment artifacts, or configuration management systems.
Question 5:
You need to return a JSON array that contains several literal values in a fixed order. Which function should you use?
A.JSON_ARRAYAGG
B.JSON_ARRAY
C.JSON_OBJECT
D.OPENJSON
Answer: B
Explanation:
Correct
B. JSON_ARRAY: This is the correct answer. The JSON_ARRAY function constructs a JSON array from a comma-separated list of values (literals, variables, or expressions) provided as arguments. It is the most direct and efficient way to format a set of specific items into a JSON array structure within a T-SQL query.
Incorrect:
A. JSON_ARRAYAGG: Incorrect. While this is also used to generate JSON arrays, it is an aggregate function. It is used to transform a set of rows into a single JSON array (e.g., aggregating values from multiple rows in a table). It does not take a fixed list of literal values as arguments in the way required by your scenario.
C. JSON_OBJECT: Incorrect. The JSON_OBJECT function is used to construct a JSON object, which consists of key-value pairs ({"key": "value"}), rather than a JSON array ([value, value]).
D. OPENJSON: Incorrect. OPENJSON is a table-valued function used for parsing or shredding existing JSON data into rows and columns. It is used for consuming or transforming JSON input, not for constructing new JSON output from literal values.
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Question 6:
You need current engine-state information such as wait statistics and cached query activity while troubleshooting performance. Which source is best?
A. RRF
B. DMVs
C. Query Store
D. JSON_OBJECT
Answer: B
Explanation:
Correct:
B. DMVs (Dynamic Management Views): This is the correct answer. DMVs are the primary diagnostic tool in SQL Server and Azure SQL for capturing a "snapshot" of the engine's current state. They provide real-time visibility into internal engine metrics, including active wait statistics (sys.dm_os_wait_stats), currently executing requests (sys.dm_exec_requests), and the current contents of the plan cache (sys.dm_exec_cached_plans). They are essential for immediate, real-time troubleshooting of performance bottlenecks.
Incorrect:
A. RRF: Incorrect. RRF (Reciprocal Rank Fusion) is a technique used in search engines and information retrieval to combine multiple ranked search result sets into one. It is completely unrelated to database engine performance monitoring or troubleshooting.
C. Query Store: Incorrect. While Query Store is an essential performance tool, it is designed for historical analysis and plan regression hunting. It stores aggregated runtime statistics over time, whereas the requirement specifically mentions "current engine-state" and "wait statistics," which are native to the live, snapshot-based nature of DMVs.
D. JSON_OBJECT: Incorrect. This is a T-SQL function used for constructing JSON data from key-value pairs. It is a formatting tool and has no diagnostic capability for monitoring database performance or system state.
Question 7:
You are deciding which chat session option to change when the current model cannot reliably return a machine-readable deployment manifest. What should you adjust first?
A. Structured output model
B. Partition switching
C. Application Insights
D. Row-Level Security
Answer: A
Explanation:
Correct
A. Structured output model: This is the correct answer. Modern LLMs and Azure AI services support Structured Outputs (often implemented via JSON schemas, Pydantic models, or specific API response format parameters). When a model struggles to return a valid, machine-readable manifest (like a JSON object), the primary remediation is to enforce a schema. By configuring the model to use a structured output mode, you restrict the generation to a defined format, ensuring the response is always valid, parseable JSON that adheres to your required manifest structure.
Incorrect:
B. Partition switching: Incorrect. Partition switching is a SQL Server feature used for high-performance data management (moving data between partitions in a table). It is a database storage optimization technique and has no impact on the quality, format, or reliability of an AI model's output.
C. Application Insights: Incorrect. Application Insights is an observability and monitoring tool. While it is excellent for detecting that the model is failing to return valid JSON (by logging the errors), it does not provide a mechanism to fix the output generation behavior of the model.
D. Row-Level Security (RLS): Incorrect. Row-Level Security is a database security feature used to restrict which rows a user can access in a table. It is entirely unrelated to the generation or formatting of AI model responses.
Question 8:
You need tamper-evident history for records, while a separate requirement asks for who performed access and change operations. Which feature addresses the tamper-evident part?
A. Database auditing
B. Change Tracking
C. Dynamic Data Masking
D. Ledger table
Answer: D
Explanation:
Correct:
D. Ledger table: This is the correct answer. Azure SQL Database Ledger tables are specifically designed to provide tamper-evident history. They use cryptographic hash chains to ensure that every insert, update, and delete operation is recorded in a way that is verifiable and immutable. Even a database administrator with high-level privileges cannot modify or delete historical data without breaking the hash chain, which can be verified at any time to ensure the integrity of the data.
Incorrect:
A. Database auditing: Incorrect. Database auditing is used to track and log database events (who accessed or modified data). While it provides a log of "who did what," it is not inherently "tamper-evident" in the cryptographic sense required to prove that historical records have not been altered after the fact.
B. Change Tracking: Incorrect. Change Tracking is a lightweight solution for identifying that data has changed in a table. It does not store the full history of the data changes (like the previous values), nor does it provide any cryptographic mechanisms to prove that the history has not been tampered with.
C. Dynamic Data Masking: Incorrect. Dynamic Data Masking is a security feature used to obfuscate sensitive data (like masking a social security number) in the result set for unauthorized users. It is a presentation-layer security feature and has no functionality related to tracking data history or ensuring data integrity.
Question 9:
A client needs to request exactly the fields and relationships it wants from one endpoint rather than multiple fixed REST payloads. Which endpoint style is the best fit?
A. Change Tracking
B. GraphQL endpoint
C. Database auditing
D. REST endpoint
Answer: B
Explanation:
B. GraphQL endpoint: This is the correct answer. GraphQL is a query language for APIs that enables clients to request precisely the data they need and nothing more. Unlike traditional REST, which often results in "over-fetching" (getting more data than needed) or "under-fetching" (requiring multiple round-trips to related endpoints), GraphQL allows the client to define the structure of the response, including nested relationships, in a single request. This is highly efficient for AI-driven applications that need specific, shaped data for model inference.
Incorrect:
A. Change Tracking: Incorrect. Change Tracking is a database-level feature in SQL Server used to capture information about which rows were modified. It is an infrastructure feature, not an API design pattern or endpoint style.
C. Database auditing: Incorrect. Database auditing is a security and compliance feature used to log events and activities within the database. It is not a method for designing API interfaces or handling client data requests.
D. REST endpoint: Incorrect. REST (Representational State Transfer) endpoints are typically defined by fixed structures. To get different fields or related data, a client usually has to call different endpoints or manage complex query parameters, which is exactly the limitation the question aims to solve.
Question 10:
A service account needs read access to one table and nothing else. Which approach is preferable?
A. db_datareader
B. Columnstore index
C. SQL authentication
D. Object-level permissions
Answer: D
Explanation:
Correct
D. Object-level permissions: This is the correct answer. Adhering to the Principle of Least Privilege is a fundamental requirement for the DP-800 exam. By using object-level permissions (e.g., GRANT SELECT ON SchemaName.TableName TO UserName), you ensure the service account has access only to the specific object it needs, rather than broad access to the entire database. This minimizes the security surface area and prevents unauthorized access to other tables containing sensitive data.
Incorrect
A. db_datareader: Incorrect. db_datareader is a fixed database role that grants SELECT permission on all user tables and views in the database. Using this role violates the principle of least privilege, as the service account would gain visibility into data it does not need, which is considered poor security practice in production environments.
B. Columnstore index: Incorrect. A Columnstore index is a performance optimization and storage technology used to improve query speed and data compression for large analytical workloads. It has absolutely no function related to security, access control, or permission management.
C. SQL authentication: Incorrect. SQL authentication relates to how a principal connects to the database (using a username and password), not what that principal is allowed to do once connected. Relying on SQL authentication also contradicts modern security recommendations (such as using Managed Identities or Entra ID) and does not inherently restrict access to specific tables.
For a full set of 175 questions. Go to
https://skillcertpro.com/product/microsoft-sql-ai-developer-dp-800-exam-questions/
SkillCertPro offers detailed explanations to each question which helps to understand the concepts better.
It is recommended to score above 85% in SkillCertPro exams before attempting a real exam.
SkillCertPro updates exam questions every 2 weeks.
You will get life time access and life time free updates
SkillCertPro assures 100% pass guarantee in first attempt.