DP-800 Practice Tests & Valid DP-800 Test Duration

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Microsoft DP-800 Exam Syllabus Topics:

Section	Weight	Objectives
Implement AI capabilities in database solutions	25-30%	- Build intelligent search and retrieval 1. Implement semantic search and RAG patterns 2. Design and implement embedding pipelines 3. Optimize search performance and relevance - Use AI-assisted development tools 1. Validate and test AI-enhanced solutions 2. Leverage AI tools for T-SQL development - Integrate AI models and services 1. Integrate with Azure AI services and Microsoft Foundry 2. Create and manage external models 3. Implement vector data and embeddings
Secure, optimize, and deploy database solutions	35-40%	- Optimize performance and reliability 1. Optimize queries and indexes 2. Ensure high availability and disaster recovery 3. Monitor and troubleshoot performance - Secure database solutions 1. Implement compliance and auditing 2. Protect data at rest and in transit 3. Implement authentication and authorization - Deploy and maintain solutions 1. Implement CI/CD for databases 2. Manage updates and versioning 3. Deploy across SQL Server, Azure SQL, and Microsoft Fabric
Design and develop database solutions	35-40%	- Design database solutions 1. Design solutions for structured and semi-structured data 2. Design for scalability and performance 3. Design for maintainability and DevOps integration - Develop database solutions 1. Implement database objects and structures 2. Implement data integration and transformation 3. Write and optimize T-SQL code

Section

Weight

Objectives

Implement AI capabilities in database solutions

25-30%

- Build intelligent search and retrieval

1. Implement semantic search and RAG patterns
2. Design and implement embedding pipelines
3. Optimize search performance and relevance

- Use AI-assisted development tools

1. Validate and test AI-enhanced solutions
2. Leverage AI tools for T-SQL development

- Integrate AI models and services

1. Integrate with Azure AI services and Microsoft Foundry
2. Create and manage external models
3. Implement vector data and embeddings

Secure, optimize, and deploy database solutions

35-40%

- Optimize performance and reliability

1. Optimize queries and indexes
2. Ensure high availability and disaster recovery
3. Monitor and troubleshoot performance

- Secure database solutions

1. Implement compliance and auditing
2. Protect data at rest and in transit
3. Implement authentication and authorization

- Deploy and maintain solutions

1. Implement CI/CD for databases
2. Manage updates and versioning
3. Deploy across SQL Server, Azure SQL, and Microsoft Fabric

Design and develop database solutions

35-40%

- Design database solutions

1. Design solutions for structured and semi-structured data
2. Design for scalability and performance
3. Design for maintainability and DevOps integration

- Develop database solutions

1. Implement database objects and structures
2. Implement data integration and transformation
3. Write and optimize T-SQL code

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Microsoft Developing AI-Enabled Database Solutions Sample Questions (Q88-Q93):

NEW QUESTION # 88
Hotspot Question
You have a SQL database in Microsoft Fabric that uses the default settings for a newly created database and contains a table named Sales.Orders.
You have an application that uses two stored procedures to access Sales.Orders.
While monitoring database activity, you discover the following:
- sys.dm_exec_requests shows multiple sessions in a suspended state
with wait_type = LCK_M_X. All the sessions show the same wait_resource, which maps to Sales.Orders, and the same nonzero blocking_session_id.
- sys.dm_exec_input_buffer(blocking_session_id, NULL) returns a last
submitted command of BEGIN TRANSACTION UPDATE Sales.Orders.
- sys.dm_exec_sessions for the blocking session shows status = sleeping and open_transaction_count = 1.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 89
You have a SQL database in Microsoft Fabric that contains a column named Payload. pay load stores customer data in JSON documents that have the following format.

Data analysis shows that some customers have subaddressing in their email address, for example, user1+promo@contoso.com.
You need to return a normalized email value that removes the subaddressing, for example, user! + promo@contoso.com must be normalized to userl@contoso.com.
Which Transact SQL expression should you use?

A. REGEXP_REPLACE(JSON_VALUE(Payload, ' $.customer_email ' ), ' \+.* ' , ' ' )
B. REGEXP_REPLACE(JSON_VALUE(Payload, ' $.customer_email ' ), ' \+.*@ ' , ' @ ' )
C. REGEXP_REPLACE(JSON_VALUE(Payload, ' $.customer_email ' ), ' \+.*$ ' , ' ' )
D. REGEXP_SUBSTR(JSON_VALUE(Payload, ' $.customer_email ' ), '