DP-800
Developing AI-Enabled Database Solutions
DP-800 Training Course
Description
DP-800: Developing AI-Enabled Database Solutions Training Course
Build practical readiness for designing Microsoft SQL database solutions that are secure, performant, deployable, observable, and prepared for AI-enabled retrieval and generation workflows.
The DP-800 Training Course prepares learners for the Developing AI-Enabled Database Solutions exam through scenario-based study of SQL Server, Azure SQL, and Microsoft Fabric SQL databases. Using AAAdemy Atomic Deconstruction, the course breaks each topic into operational layers, component specifications, step-by-step execution paths, and exam-ready validation workflows.
Strategic Focus on AI-Enabled SQL Database Solutions
Database design: Tables, constraints, specialized table types, JSON access, sequences, partitions, indexes, views, functions, procedures, triggers, CTEs, window functions, graph queries, regex, and fuzzy matching.
Security and deployment: Always Encrypted, Dynamic Data Masking, Row-Level Security, object permissions, passwordless access, auditing, managed identity, secure endpoints, SQL Database Projects, branch controls, tests, secrets, and drift review.
Performance and observability: Query Store, DMVs, execution plans, blocking, deadlocks, isolation levels, Azure Monitor, Application Insights, Log Analytics, endpoint telemetry, and change processing.
AI data path: External models, embeddings, chunking, vector columns, vector indexes, full-text search, vector search, hybrid retrieval, ANN/ENN evaluation, RRF, JSON conversion, external REST invocation, and RAG grounding.
Task-Oriented & Scenario-Based Learning
Learners practice with Operational Skills Matrix checks, evidence-first troubleshooting, platform boundary review, deployment validation, search-quality evaluation, and grounded-answer verification. The DP-800 training course emphasizes why an action is correct, why distractors are lower priority, and how to prove the database or AI workflow state before changing production systems.
Table of Contents
1. Study Plan for DP-800 Exam
2. DP-800 Study Methods and Key Points
3. DP-800 Knowledge Explanation
Design and develop database solutions
Secure, optimize, and deploy database solutions
Implement AI capabilities in database solutions
4. Practice Questions and Answers
Knowledge Points & Frequently Asked Questions
1. Design and develop database solutions
- Q1: When a DP-800 scenario says a query became slow after JSON attributes were added to a high-volume table, what should be checked first?
- Q2: How should a designer decide between a SEQUENCE and an IDENTITY column for generated keys?
- Q3: When should specialized table types such as temporal, ledger, graph, or in-memory tables be selected?
2. Secure, optimize, and deploy database solutions
- Q1: What is the safest first step when a data endpoint returns more rows than expected to an application?
- Q2: When a production SQL workload shows blocking, deadlocks, or high latency, what evidence should be collected before resizing the database?
- Q3: Why are least-privilege permissions important when exposing SQL data through Data API builder or similar endpoint layers?
3. Implement AI capabilities in database solutions
- Q1: How should a database team design embedding storage for SQL-based AI search?
- Q2: When should full-text search, vector search, semantic search, or hybrid search be used?
- Q3: What should be checked first when vector search returns stale or irrelevant results after source data changes?
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