Microsoft · DP-800
Validates expertise in designing and developing AI-enabled database solutions across Microsoft SQL platforms including SQL Server, Azure SQL, and SQL databases in Microsoft Fabric. Covers T-SQL development, CI/CD practices, security, performance optimization, and implementing AI capabilities such as vector search and RAG.
Practice Questions
600
≈ 12 practice exams
Duration
100 minutes
Passing Score
700/1000
Difficulty
AssociateLast Updated
May 2026
Use this DP-800 practice exam to prepare for Microsoft Certified: SQL AI Developer Associate (DP-800) with realistic questions, detailed explanations, and focused study modes. The practice bank includes 600 questions for Microsoft DP-800, so you can review the exam steadily instead of relying on one long cram session.
As you practice, pay extra attention to recurring topics such as Design and Develop Database Solutions, Implement Programmability Objects, Write Advanced T-SQL Code, AI-Assisted SQL Development Tools, and Data Security and Compliance. Start with short sessions to identify weak areas, then move into timed quizzes once your accuracy is consistent.
The explanations are especially useful when you want to connect exam wording to the responsibilities and scenarios described in the official certification guidance. Use the free preview first, then unlock the full question bank when you are ready to build a complete study routine.
The Microsoft Certified: SQL AI Developer Associate certification, earned by passing Exam DP-800 (Developing AI-Enabled Database Solutions), validates expertise in designing and building AI-enabled database solutions across the full breadth of Microsoft SQL platforms—Microsoft SQL Server, Azure SQL, and SQL databases in Microsoft Fabric. The credential covers the complete lifecycle of modern database development: schema design, advanced T-SQL programming, performance optimization, data security, CI/CD automation via SQL Database Projects, and deep integration with Azure services such as Data API builder (DAB), Azure Monitor, and Azure Functions.
Released in early 2026, the certification reflects the industry shift toward embedding AI directly inside the database tier rather than relying solely on external AI services. Candidates must demonstrate practical knowledge of AI-assisted development tooling (GitHub Copilot, Microsoft Copilot in Fabric, Model Context Protocol), as well as core AI concepts—vector embeddings, semantic search, hybrid search, and Retrieval-Augmented Generation (RAG) using native T-SQL functions and the sp_invoke_external_rest_endpoint stored procedure.
This certification targets mid-level database developers—typically with two or more years of hands-on T-SQL experience—who are expanding into AI-integrated and cloud-scale architectures. Ideal candidates hold roles such as SQL/database developer, Azure SQL developer, data engineer, or backend application developer who owns the database layer. Professionals working with Microsoft Fabric, Azure SQL Database, or SQL Server who need to expose intelligent search or natural-language interfaces to applications are a natural fit.
Candidates collaborate daily with application developers, DBAs, architects, AI engineers, DevSecOps engineers, and security administrators. Some exposure to GitHub-based CI/CD workflows and foundational AI concepts (embeddings, vectors, language models) is expected before attempting the exam.
Microsoft does not enforce formal prerequisites for DP-800, but the exam assumes solid practical experience. Candidates should be comfortable writing complex T-SQL including CTEs, window functions, JSON functions, and stored procedures before studying the AI-specific content. Familiarity with database design fundamentals—indexes, constraints, partitioning, row-level security, Always Encrypted, and Dynamic Data Masking—is assumed throughout.
On the tooling side, experience with GitHub (branching, pull requests, Actions) and a working knowledge of Azure services such as Azure Functions, Logic Apps, and Azure Monitor will reduce the learning curve significantly. Exposure to AI/ML concepts—particularly what embeddings are, how vector similarity works, and what a language model prompt looks like—is recommended. Microsoft's free self-paced learning path 'Become a SQL AI Developer: Prepare for Certification Exam DP-800' on Microsoft Learn can fill gaps in any of these areas.
Exam DP-800 is a proctored assessment delivered through Pearson VUE, available in English. Candidates have 120 minutes to complete the exam (the official certification page specifies 120 minutes; allow approximately 100 minutes of active test time). The exam may include interactive lab or scenario-based components in addition to standard multiple-choice and multi-select question types. Candidates can explore the user interface in advance using Microsoft's free Exam Sandbox at aka.ms/examdemo.
A scaled score of 700 or higher (on a 1–1000 scale) is required to pass. If a candidate fails the first attempt, they must wait 24 hours before retaking; subsequent retake intervals vary per Microsoft's standard retake policy. The certification is valid for one year and can be renewed at no cost via an online assessment on Microsoft Learn. Exam price varies by country/region as set by Pearson VUE.
The SQL AI Developer Associate credential positions holders at the intersection of two high-demand skill sets—enterprise SQL development and applied AI engineering—making them valuable to organizations adopting Microsoft Fabric, Azure SQL, or SQL Server 2022+ for intelligent application backends. Roles commonly associated with this certification include SQL/Database Developer, Azure Data Engineer, Backend Developer, and AI Integration Engineer. Because the certification is new (2026), early adopters gain a differentiation advantage as enterprises ramp up AI-enabled data architectures across regulated industries such as finance, healthcare, and retail.
While Microsoft does not publish salary data tied to specific certifications, data engineers and database developers with Azure AI skills command salaries in the $110,000–$145,000 range in the US market (2025–2026 surveys), with premiums for Fabric and AI integration experience. The DP-800 complements adjacent certifications such as DP-300 (Azure Database Administrator Associate) and DP-700 (Fabric Data Engineer Associate), and serves as a natural progression for SQL professionals who have outgrown purely administrative or ETL-focused roles and want to build AI-powered data products.
5 sample questions with answers and explanations. The full bank has 600 questions, enough for 12 full-length practice exams.
Preview — answers shown1. A security team at Fabrikam Healthcare must capture all SELECT, INSERT, UPDATE, and DELETE operations on the PatientData schema in Azure SQL Database. The captured logs must support long-term retention and direct integration with Microsoft Sentinel for security incident analysis. Which audit destination should the team configure? (Select one!)
Explanation
A Log Analytics workspace is the correct destination because Microsoft Sentinel is built on top of Log Analytics, making it the native integration point for security information and event management workflows. Audit data written to Log Analytics is immediately queryable by Sentinel analytics rules, workbooks, and hunting queries without requiring additional connectors or data movement. Azure Blob Storage provides cost-effective long-term storage but does not offer native Sentinel integration; connecting them requires configuring a custom data connector. Azure Event Hub is designed for high-throughput real-time streaming to downstream consumers and does not provide built-in log retention or direct Sentinel query capabilities. Extended Events session file targets are primarily an on-premises diagnostic mechanism and are not a supported Azure SQL Database audit destination.
2. A developer at Litware Inc. is building a data validation pipeline in a SQL Server 2025 database running at compatibility level 170. They must validate that email address strings match a defined pattern and also replace phone number patterns embedded within a freetext notes column. Which two T-SQL functions should the developer use for these respective tasks? (Select two!)
Multiple correct answersExplanation
REGEXP_LIKE evaluates whether a string matches a regular expression pattern and returns TRUE or FALSE, making it the correct choice for email format validation. REGEXP_REPLACE replaces all occurrences of a matched pattern within a string with a specified replacement value, which is the correct choice for sanitizing or transforming phone number patterns embedded in freetext columns. Both functions require database compatibility level 170 or higher and use the RE2 regular expression engine. EDIT_DISTANCE_SIMILARITY and JARO_WINKLER_DISTANCE are fuzzy string matching functions that measure similarity between two strings based on edit operations or prefix weighting, not pattern-based validation or replacement. REGEXP_COUNT counts the number of times a pattern appears in a string but cannot validate or replace matched content.
3. A developer at Contoso is maintaining a SQL Server 2025 database whose compatibility level is set to 160 due to legacy application constraints that prevent the DBA team from upgrading it. The developer needs to introduce regex-based data cleansing logic using native T-SQL functions. Which two regular expression functions can be used without changing the database compatibility level? (Select two!)
Multiple correct answersExplanation
In SQL Server 2025, the seven native regular expression functions are split into two groups based on compatibility level requirements. REGEXP_COUNT, REGEXP_INSTR, REGEXP_SUBSTR, and REGEXP_REPLACE are scalar functions available at any database compatibility level when running on SQL Server 2025, meaning they work even if the database is still at level 130, 140, 150, or 160. REGEXP_LIKE, REGEXP_MATCHES, and REGEXP_SPLIT_TO_TABLE each require compatibility level 170 or higher to be recognized by the query engine. Because the Contoso database is at level 160, REGEXP_REPLACE and REGEXP_COUNT can be called immediately without any ALTER DATABASE statement. REGEXP_LIKE would fail with an unrecognized function error at level 160. REGEXP_MATCHES and REGEXP_SPLIT_TO_TABLE are table-valued functions that also require level 170 and would similarly be unavailable. The RE2 library that powers all seven functions is installed as part of SQL Server 2025 and does not require separate configuration regardless of compatibility level.
4. A developer at Humongous Insurance is implementing database auditing for an Azure SQL Database instance. The security team requires that all DML operations on the Claims table be streamed in real time to the company's SIEM platform for threat detection. The SIEM platform supports native ingestion from Azure Event Hubs. Which audit destination should the developer configure? (Select one!)
Explanation
Azure Event Hub is designed for high-throughput, real-time event streaming and integrates natively with SIEM platforms and analytics pipelines. Configuring Azure SQL Database auditing to target an Event Hub enables the security team to consume and analyze audit records in real time as they are produced. Azure Blob Storage stores audit logs as flat files suitable for long-term retention and batch analysis, but does not provide real-time event streaming to external consumers. Azure Monitor Metrics captures numeric telemetry such as CPU utilization and DTU consumption, not SQL audit event records. Azure Log Analytics is well suited for log aggregation, ad hoc querying, and alerting on audit data, but is optimized for offline analysis rather than real-time streaming to external SIEM systems.
5. A developer at Proseware Inc. is writing a CREATE EXTERNAL MODEL statement to register a locally hosted Ollama embedding endpoint for development use in Azure SQL Database. The Ollama instance does not require authentication, and the developer does not need to customize the request payload. Which two parameters in the CREATE EXTERNAL MODEL statement are optional and can be omitted without causing the statement to fail? (Select two!)
Multiple correct answersExplanation
CREDENTIAL and PARAMETERS are both optional parameters in CREATE EXTERNAL MODEL and can be omitted when not needed. CREDENTIAL specifies the DATABASE SCOPED CREDENTIAL object used for authenticating to the AI model inference endpoint. For locally hosted endpoints such as Ollama that do not require authentication, CREDENTIAL can be omitted entirely from the WITH clause. PARAMETERS accepts a valid JSON string containing runtime parameters appended to the endpoint request message, such as specifying output vector dimensions. When no custom request configuration is required, PARAMETERS can be omitted. LOCATION is required in every CREATE EXTERNAL MODEL statement because it provides the connectivity protocol and full path to the AI model inference endpoint. Without a LOCATION value the database engine has no URL to send embedding requests to. API_FORMAT is required because it defines how the database engine structures HTTP request payloads and parses HTTP responses. Accepted values include Azure OpenAI, OpenAI, Ollama, and ONNX Runtime. Each produces a different request message format, and omitting API_FORMAT causes the statement to fail with a syntax error. MODEL_TYPE is required because it declares the intended purpose of the registered model. The only currently accepted value is EMBEDDINGS, which configures the engine to invoke the endpoint for vector embedding generation. Omitting MODEL_TYPE causes a syntax error in the CREATE EXTERNAL MODEL statement.
DP-800 is one of Microsoft's newest role-based exams, which means leaked-question sources have had almost no time to accumulate anything close to accurate content. What they do have working against them is Microsoft's Candidate Agreement: using unauthorized exam content risks revocation across every Microsoft certification you hold, not just DP-800.
On a fast-moving exam like this, current and accurate practice material matters more than usual. CertCompanion's DP-800 bank has 600 practice questions, 30 free, built around Microsoft's published SQL AI Developer skills outline.
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