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Microsoft DP-600 Exam Syllabus Topics:

Section	Weight	Objectives
Implement and manage semantic models	25–30	- Deploy and maintain semantic models 1. Use XMLA endpoint for deployment and management 2. Create reusable assets and shared models 3. Monitor and refresh semantic models - Design and build semantic models 1. Optimize model performance and structure 2. Define relationships, hierarchies, and measures 3. Create Power BI semantic models
Prepare data for analytics	45–50	- Clean and transform data 1. Perform data enrichment and validation 2. Process data using Spark notebooks and SQL 3. Manage data quality and consistency - Implement data storage structures 1. Design and manage lakehouse tables 2. Configure warehouse storage and querying 3. Implement delta lake and partitioning - Ingest and load data 1. Use Dataflows Gen2 to transform data 2. Ingest data from various sources 3. Load data into lakehouses and warehouses
Maintain a data analytics solution	25–30	- Manage analytics development lifecycle 1. Configure version control and projects 2. Implement deployment pipelines 3. Perform impact analysis and dependency management - Implement security and governance 1. Configure workspace and item-level access 2. Use sensitivity labels and endorsement 3. Apply row-level, column-level, and object-level security

Section

Weight

Objectives

Implement and manage semantic models

25–30

- Deploy and maintain semantic models

1. Use XMLA endpoint for deployment and management
2. Create reusable assets and shared models
3. Monitor and refresh semantic models

- Design and build semantic models

1. Optimize model performance and structure
2. Define relationships, hierarchies, and measures
3. Create Power BI semantic models

Prepare data for analytics

45–50

- Clean and transform data

1. Perform data enrichment and validation
2. Process data using Spark notebooks and SQL
3. Manage data quality and consistency

- Implement data storage structures

1. Design and manage lakehouse tables
2. Configure warehouse storage and querying
3. Implement delta lake and partitioning

- Ingest and load data

1. Use Dataflows Gen2 to transform data
2. Ingest data from various sources
3. Load data into lakehouses and warehouses

Maintain a data analytics solution

25–30

- Manage analytics development lifecycle

1. Configure version control and projects
2. Implement deployment pipelines
3. Perform impact analysis and dependency management

- Implement security and governance

1. Configure workspace and item-level access
2. Use sensitivity labels and endorsement
3. Apply row-level, column-level, and object-level security

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楽にMicrosoft DP-600認定試験の準備を完了したい？

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric 認定 DP-600 試験問題 (Q142-Q147):

質問 # 142
You have a Fabric workspace that contains a warehouse named Warehouse!. Warehousel contains the following data.

You need to create a T-SQL statement that will denormalize the tables and include the ContractType and StartDate attributes in the results. The solution must meet the following requirements:
* Include attributes from matching rows in the Contract table.
* Ensure that all the rows from the Employee table are preserved.
* Return the total number of employees per contract type for all the contract types that have more than two employees.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

Explanation:

質問 # 143
You have a Fabric warehouse that contains a table named Sales.Products. Sales.Products contains the following columns.

You need to write a T-SQL query that will return the following columns.

How should you complete the code? To answer, select the appropriate options in the answer area.

正解：

解説：

Explanation:
For the HighestSellingPrice, you should use the GREATEST function to find the highest value from the given price columns. However, T-SQL does not have a GREATEST function as found in some other SQL dialects, so you would typically use a CASE statement or an IIF statement with nested MAX functions. Since neither of those are provided in the options, you should select MAX as a placeholder to indicate the function that would be used to find the highest value if combining multiple MAX functions or a similar logic was available.
For the TradePrice, you should use the COALESCE function, which returns the first non-null value in a list.
The COALESCE function is the correct choice as it will return AgentPrice if it ' s not null; if AgentPrice is null, it will check WholesalePrice, and if that is also null, it will return ListPrice.
The complete code with the correct SQL functions would look like this:
SELECT ProductID,
MAX(ListPrice, WholesalePrice, AgentPrice) AS HighestSellingPrice, -- MAX is used as a placeholder COALESCE(AgentPrice, WholesalePrice, ListPrice) AS TradePrice FROM Sales.Products Select MAX for HighestSellingPrice and COALESCE for TradePrice in the answer area.

質問 # 144
You have a Fabric tenant that contains a workspace named Workspace

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