Try 12 Microsoft Certified: SQL AI Developer Associate (DP-800) sample questions and practice-test preview prompts on AI-enabled database solutions, SQL Server, Azure SQL, modernization, security, and performance decisions.
DP-800 is a Microsoft SQL route for developers designing and developing AI-enabled database solutions across Microsoft SQL platforms.
IT Mastery coverage for DP-800 is under review. Use this page to try 12 original sample questions, review the route fit, likely assessed areas, and related live practice pages.
Practice option: Sample questions available
Start with the 12 sample questions on this page. Dedicated practice for DP-800: Developing AI-Enabled Database Solutions is not currently included as a full web-app practice page; enter your email to get updates when full practice becomes available or expands for this exam.
Need live practice now? See currently available IT Mastery exam pages.
| Area | Practical focus |
|---|---|
| Database development | Review schema design, T-SQL, programmability, indexing, and deployment choices. |
| AI-enabled SQL | Connect vectors, embeddings, model endpoints, and retrieval patterns to SQL workloads. |
| Security and DevOps | Review secure access, CI/CD, drift, permissions, and monitoring. |
| If you need practice now | Start here |
|---|---|
| Oracle SQL 1Z0-071 | Live SQL fundamentals-style practice. |
| DP-700 Fabric Data Engineer | Adjacent Microsoft data engineering route. |
| GitHub Actions | Useful for database CI/CD workflow context. |
Try these 12 original sample questions for Microsoft DP-800. They are designed for self-assessment and are not official exam questions.
Topic: AI-enabled SQL
A product-search feature needs semantic similarity over descriptions stored in SQL. What should be evaluated?
Best answer: A
Explanation: DP-800 focuses on AI-enabled database solutions, including retrieval patterns around SQL data.
What this tests: Designing AI-enabled SQL features.
Topic: schema design
An app stores customers, orders, and line items. What should guide schema design?
Best answer: B
Explanation: Database development starts with schema design that supports integrity and workload needs.
What this tests: Designing relational schemas.
Topic: T-SQL programmability
A repeated calculation must run consistently near the data. What might be used?
Best answer: C
Explanation: SQL development includes programmable database objects when they fit maintainability and performance needs.
What this tests: Using SQL programmability.
Topic: security
An application should read customer records but not alter billing tables. What should be configured?
Best answer: D
Explanation: Database security should grant only required permissions to application identities.
What this tests: Securing SQL data access.
Topic: retrieval augmented generation
A chatbot should answer from approved SQL product data. What should the design include?
Best answer: A
Explanation: AI-enabled database solutions must connect retrieval, permissions, and response quality.
What this tests: Grounding AI with SQL data.
Topic: indexing
A query used by an AI retrieval service is slow. What should be reviewed?
Best answer: B
Explanation: SQL performance tuning still matters when AI applications use database-backed retrieval.
What this tests: Optimizing SQL query performance.
Topic: DevOps
Database changes break production because scripts are applied manually. What should be introduced?
Best answer: C
Explanation: DP-800 includes secure and reliable database development practices.
What this tests: Applying DevOps to databases.
Topic: data quality
An AI feature gives bad recommendations because product categories are inconsistent. What should be fixed?
Best answer: D
Explanation: AI output quality depends on database quality and consistent source data.
What this tests: Connecting data quality to AI behavior.
Topic: monitoring
An AI-enabled SQL app shows rising latency. What should be monitored?
Best answer: A
Explanation: Latency may occur in database queries or AI orchestration. Monitoring should cover both.
What this tests: Monitoring AI-enabled database workloads.
Topic: deployment drift
Production schema differs from source control. What is the risk?
Best answer: B
Explanation: Schema drift makes database delivery harder to trust and maintain.
What this tests: Understanding deployment drift.
Topic: privacy
A prompt includes raw customer PII from SQL rows. What should be reviewed?
Best answer: C
Explanation: AI-enabled database solutions need privacy and data-protection controls.
What this tests: Protecting sensitive SQL data in AI workflows.
Topic: route fit
A candidate designs SQL database solutions with AI retrieval, security, T-SQL, and DevOps. Which route is closest?
Best answer: D
Explanation: DP-800 is the Developing AI-Enabled Database Solutions route.
What this tests: Choosing the Microsoft SQL AI-enabled database route.
Use this map to connect the sample questions to AI-enabled SQL development decisions.
flowchart LR
S1["Application data need"] --> S2
S2["Design SQL schema and programmability"] --> S3
S3["Add embeddings or AI integration"] --> S4
S4["Secure access and secrets"] --> S5
S5["Deploy with CI and monitoring"] --> S6
S6["Tune performance and quality"]
| Cue | What to remember |
|---|---|
| SQL design | Keep schema, indexes, constraints, and query patterns aligned with application behavior. |
| AI integration | Use embeddings, vector search, retrieval, or model calls only where they add value. |
| Security | Protect credentials, permissions, sensitive data, and service access paths. |
| DevOps | Version database changes, test migrations, and monitor drift. |
| Performance | Watch query plans, indexes, vector search cost, and workload telemetry. |
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