DP-600のPDF問題集リアル2026最近更新された問題
リリースMicrosoft DP-600更新された問題PDF
質問 # 37
You have source data in a folder on a local computer.
You need to create a solution that will use Fabric to populate a data store. The solution must meet the following requirements:
* Support the use of dataflows to load and append data to the data store.
* Ensure that Delta tables are V-Order optimized and compacted automatically.
Which type of data store should you use?
- A. a KQL database
- B. a warehouse
- C. an Azure SQL database
- D. a lakehouse
正解：D
質問 # 38
You need to migrate the Research division data for Productline2. The solution must meet the data preparation requirements. How should you complete the code? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Comprehensive Detailed Explanation
From the case study:
Research division data for Productline2 is currently in CSV format in storage2.
Requirement: "All the Research division data in the lakehouses must be presented as managed tables in Lakehouse explorer." In Fabric lakehouses, managed tables are stored in Delta format inside the Tables folder.
Step 1: Reading the source
df = spark.read.format("csv") \
options(header="true", inferSchema="true") \
load("abfss://storage1.dfs.core.windows.net/files/productline2")
This correctly ingests the CSV source from ADLS Gen2.
Step 2: Writing to Lakehouse as a managed table
You must write the data in Delta format to ensure it is queryable and managed within the lakehouse.
The correct path is under Tables/, because this is where Fabric automatically manages Lakehouse managed tables.
The target table should be named productline2, so the correct path is:
df.write.mode("overwrite").format("delta").save("Tables/productline2")
Why not other options?
CSV or Parquet formats would not create a managed Lakehouse table; they would just create files.
Writing to productline2 directly (without Tables/) would store unmanaged files in the Lakehouse Files area, not managed tables.
Writing to Tables/research/productline2 adds an unnecessary subdirectory and is not the standard structure for managed tables.
Correct Final Code
df.write.mode("overwrite").format("delta").save("Tables/productline2")
References
Managed tables in Microsoft Fabric Lakehouse
Delta Lake support in Fabric
Spark write to Lakehouse
質問 # 39
You have a Fabric tenant that contains a new semantic model in OneLake.
You use a Fabric notebook to read the data into a Spark DataFrame.
You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.
Solution: You use the following PySpark expression:
df.show()
Does this meet the goal?
- A. Yes
- B. No
正解：B
解説：
The df.show() method also does not meet the goal. It is used to show the contents of the DataFrame, not to compute statistical functions. Reference = The usage of the show() function is documented in the PySpark API documentation.
質問 # 40
Which workspace rote assignments should you recommend for ResearchReviewersGroupl and ResearchReviewersGroupZ? 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 # 41
You have a Fabric tenant that contains a semantic model.
You need to prevent report creators from populating visuals by using implicit measures.
What are two tools that you can use to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.
- A. DAX Studio
- B. Tabular Editor
- C. Microsoft SQL Server Management Studio (SSMS)
- D. Microsoft Power BI Desktop
正解：B、D
解説：
To prevent report creators from populating visuals using implicit measures in a Power BI semantic model within a Fabric tenant, you can utilize the following tools:
1. Tabular Editor:
2. Power BI Desktop (Data Model View):
質問 # 42
You have a Fabric tenant that contains a lakehouse named lakehouse1. Lakehouse1 contains a table named Table1.
You are creating a new data pipeline.
You plan to copy external data to Table1. The schema of the external data changes regularly.
You need the copy operation to meet the following requirements:
* Replace Table1 with the schema of the external data.
* Replace all the data in Table1 with the rows in the external data.
You add a Copy data activity to the pipeline. What should you do for the Copy data activity?
- A. From the Settings tab, select Enable staging
- B. From the Source tab, select Recursively
- C. From the Source tab, add additional columns.
- D. From the Destination tab, set Table action to Overwrite.
- E. From the Source tab, select Enable partition discovery
正解：D
解説：
For the Copy data activity, from the Destination tab, setting Table action to Overwrite (B) will ensure that Table1 is replaced with the schema and rows of the external data, meeting the requirements of replacing both the schema and data of the destination table. Reference = Information about Copy data activity and table actions in Azure Data Factory, which can be applied to data pipelines in Fabric, is available in the Azure Data Factory documentation.
質問 # 43
Case Study 1 - Contoso
Overview
Contoso, Ltd. is a US-based health supplements company. Contoso has two divisions named Sales and Research. The Sales division contains two departments named Online Sales and Retail Sales. The Research division assigns internally developed product lines to individual teams of researchers and analysts.
Existing Environment
Identity Environment
Contoso has a Microsoft Entra tenant named contoso.com. The tenant contains two groups named ResearchReviewersGroup1 and ResearchReviewersGroup2.
Data Environment
Contoso has the following data environment:
- The Sales division uses a Microsoft Power BI Premium capacity.
- The semantic model of the Online Sales department includes a fact table named Orders that uses Import made. In the system of origin, the OrderID value represents the sequence in which orders are created.
- The Research department uses an on-premises, third-party data warehousing product.
- Fabric is enabled for contoso.com.
- An Azure Data Lake Storage Gen2 storage account named storage1 contains Research division data for a product line named Productline1. - The data is in the delta format.
- A Data Lake Storage Gen2 storage account named storage2 contains Research division data for a product line named Productline2. The data is in the CSV format.
Requirements
Planned Changes
Contoso plans to make the following changes:
- Enable support for Fabric in the Power BI Premium capacity used by the Sales division.
- Make all the data for the Sales division and the Research division available in Fabric.
- For the Research division, create two Fabric workspaces named Productline1ws and Productine2ws.
- In Productline1ws, create a lakehouse named Lakehouse1.
- In Lakehouse1, create a shortcut to storage1 named ResearchProduct.
Data Analytics Requirements
Contoso identifies the following data analytics requirements:
- All the workspaces for the Sales division and the Research division must support all Fabric experiences.
- The Research division workspaces must use a dedicated, on-demand capacity that has per- minute billing.
- The Research division workspaces must be grouped together logically to support OneLake data hub filtering based on the department name.
- For the Research division workspaces, the members of ResearchReviewersGroup1 must be able to read lakehouse and warehouse data and shortcuts by using SQL endpoints.
- For the Research division workspaces, the members of ResearchReviewersGroup2 must be able to read lakehouse data by using Lakehouse explorer.
- All the semantic models and reports for the Research division must use version control that supports branching.
Data Preparation Requirements
Contoso identifies the following data preparation requirements:
- The Research division data for Productline1 must be retrieved from Lakehouse1 by using Fabric notebooks.
- All the Research division data in the lakehouses must be presented as managed tables in Lakehouse explorer.
Semantic Model Requirements
Contoso identifies the following requirements for implementing and managing semantic models:
- The number of rows added to the Orders table during refreshes must be minimized.
- The semantic models in the Research division workspaces must use Direct Lake mode.
General Requirements
Contoso identifies the following high-level requirements that must be considered for all solutions:
- Follow the principle of least privilege when applicable.
- Minimize implementation and maintenance effort when possible.
Hotspot Question
You need to recommend a solution to group the Research division workspaces.
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
https://learn.microsoft.com/en-us/fabric/governance/domains#configure-domain-settings
質問 # 44
You have a Fabric tenant.
You plan to create a data pipeline named Pipeline1. Pipeline1 will include two activities that will execute in sequence.
You need to ensure that a failure of the first activity will NOT block the second activity.
Which conditional path should you configure between the first activity and the second activity?
- A. Upon Completion
- B. Upon Skip
- C. Upon Skip
- D. Upon Failure
正解：A
質問 # 45
You have a Fabric tenant that contains two workspaces named Workspace1 and Workspace2 and a user named User1.
You need to ensure that User1 can perform the following tasks:
* Create a new domain.
* Create two subdomains named subdomain1 and subdomain2.
* Assign Workspace1 to subdomain1.
* Assign Workspace2 to subdomain2.
The solution must follow the principle of least privilege.
Which role should you assign to User1?
- A. Workspace Admin
- B. Domain admin
- C. Domain contributor
- D. Fabric admin
正解：B
質問 # 46
You have a Fabric warehouse named Warehouse1 that contains a table named dbo.Product. dbo.Product contains the following columns.
You need to use a T-SQL query to add a column named PriceRange to dbo.Product. The column must categorize each product based on UnitPrice. The solution must meet the following requirements:
* If UnitPrice is 0, PriceRange is "Not for resale".
* If UnitPrice is less than 50, PriceRange is "Under $50".
* If UnitPrice is between 50 and 250, PriceRange is "Under $250".
* In all other instances, PriceRange is "$250+".
How should you complete the query? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Comprehensive Detailed Explanation
We need to create a computed column PriceRange based on the UnitPrice column in the dbo.Product table.
Step 1: Requirements
If UnitPrice = 0 # "Not for resale"
If UnitPrice < 50 # "Under $50"
If UnitPrice >= 50 AND UnitPrice < 250 # "Under $250"
Otherwise # "$250+"
This matches a CASE expression in T-SQL.
Step 2: CASE Expression Structure
The syntax is:
CASE
WHEN condition THEN result
WHEN condition THEN result
ELSE result
END
Step 3: Apply to Problem
SELECT
Item,
UnitPrice,
PriceRange = CASE
WHEN UnitPrice = 0 THEN 'Not for resale'
WHEN UnitPrice < 50 THEN 'Under $50'
WHEN UnitPrice >= 50 AND UnitPrice < 250 THEN 'Under $250'
ELSE '$250+'
END
FROM [Warehouse1].[dbo].[Product];
Step 4: Why This is Correct
CASE starts the conditional evaluation.
ELSE handles the default branch ($250+).
END closes the expression.
Meets all requirements exactly.
References
CASE expression in T-SQL
Computed columns in T-SQL
質問 # 47
You have a Fabric workspace named Workspace1 that contains the following items:
A warehouse named Warehouse1
A semantic model named Model1
An interactive report named Report1
You need to allow a user named User1 to access a single table in Warehouse1. The solution must follow the principle of least privilege.
What should you do first?
- A. Assign object level permissions to User1 for Warehouse1.
- B. Share Warehouse1 with User1.
- C. Assign the Viewer role to User1 for Workspace1.
- D. Assign the db_datareader role to User1 for Warehouse1.
正解：A
解説：
Requirement
Fabric workspace: Workspace1
Contains: Warehouse1, Model1, Report1
Task: Allow User1 to access a single table in Warehouse1.
Must follow principle of least privilege # grant only the exact permissions required.
Step 1: Evaluate Options
A). Assign object level permissions to User1 for Warehouse1.
In Fabric warehouses, you can grant permissions at the object level (table, schema, or column).
If the requirement is access to only one table, the correct approach is to grant SELECT permissions on that specific table.
This satisfies least privilege.
Correct. #
B). Assign the db_datareader role to User1 for Warehouse1.
db_datareader provides read access to all tables in the database/warehouse.
This violates least privilege.
Not correct.
C). Share Warehouse1 with User1.
Sharing grants access to the whole warehouse.
Too broad, not least privilege.
Not correct.
D). Assign the Viewer role to User1 for Workspace1.
Viewer role allows seeing all items in the workspace (warehouse, model, reports).
This would expose more than the single table.
Not correct.
Step 2: Correct Action
Use object-level permissions:
GRANT SELECT ON dbo.TableName TO [User1];
This ensures User1 can only query that specific table, nothing else.
References
Manage object-level security in Microsoft Fabric warehouses
Principle of least privilege in Fabric
質問 # 48
You have a Fabric warehouse that contains a table named Staging.Sales. Staging.Sales contains the following columns.
You need to write a T-SQL query that will return data for the year 2023 that displays ProductID and ProductName arxl has a summarized Amount that is higher than 10,000. Which query should you use?
- A.
- B.
- C.
- D.
正解：C
解説：
The correct query to use in order to return data for the year 2023 that displays ProductID, ProductName, and has a summarized Amount greater than 10,000 is Option B. The reason is that it uses the GROUP BY clause to organize the data by ProductID and ProductName and then filters the result using the HAVING clause to only include groups where the sum of Amount is greater than 10,000. Additionally, the DATEPART(YEAR, SaleDate) = '2023' part of the HAVING clause ensures that only records from the year 2023 are included.
References = For more information, please visit the official documentation on T-SQL queries and the GROUP BY clause at T-SQL GROUP BY.
質問 # 49
You have a Fabric warehouse that contains a table named SalesOrderDetail, SalesOrderDetail contains three columns named OrderQty, ProductID and SalesOrderlD. SalesOrderDetail contains one row per combination of SalesOrderlD and ProductID.
You need to calculate the proportion of the total quantity of each sales order represented by each product within the sales order.
Which T-SQL statement should you run?
- A.
- B.
- C.
- D.
正解：A
質問 # 50
You have two Microsoft Power Bl queries named Employee and Retired Roles.
You need to merge the Employee query with the Retired Roles query. The solution must ensure that rows in the Employee query that match the Retired Roles query are removed.
Which column and Join Kind should you use in Power Query Editor? To answer, select the appropriate options in the answer area.
NOTE: Each correct answer is worth one point
正解：
解説：
Explanation:
質問 # 51
You are analyzing the data in a Fabric notebook.
You have a Spark DataFrame assigned to a variable named df.
You need to use the Chart view in the notebook to explore the data manually.
Which function should you run to make the data available in the Chart view?
- A. display
- B. show
- C. displayMTML
- D. write
正解：A
解説：
The display function is the correct choice to make the data available in the Chart view within a Fabric notebook. This function is used to visualize Spark DataFrames in various formats including charts and graphs directly within the notebook environment. Reference = Further explanation of the display function can be found in the official documentation on Azure Synapse Analytics notebooks.
質問 # 52
You need to create a data loading pattern for a Type 1 slowly changing dimension (SCD).
Which two actions should you include in the process? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
- A. Update rows when the non-key attributes have changed.
- B. Insert new records when the natural key is a new value in the table.
- C. Update the effective end date of rows when the non-key attribute values have changed.
- D. Insert new rows when the natural key exists in the dimension table, and the non-key attribute values have changed.
正解：A、B
解説：
Type 1 SCD does not preserve history, therefore no end dates for table entries exists.
質問 # 53
You have a Fabric tenant that contains a semantic model. The model contains 15 tables.
You need to programmatically change each column that ends in the word Key to meet the following requirements:
- Hide the column.
- Set Nullable to False
- Set Summarize By to None.
- Set Available in MDX to False.
- Mark the column as a key column.
What should you use?
- A. DAX Studio
- B. Tabular Editor
- C. ALM Toolkit
- D. Microsoft Power BI Desktop
正解：B
解説：
Tabular Editor allows you to use C# scripts to automate these changes. In PBI Desktop you can do this only manually.
質問 # 54
Case Study 1 - Contoso
Overview
Contoso, Ltd. is a US-based health supplements company. Contoso has two divisions named Sales and Research. The Sales division contains two departments named Online Sales and Retail Sales. The Research division assigns internally developed product lines to individual teams of researchers and analysts.
Existing Environment
Identity Environment
Contoso has a Microsoft Entra tenant named contoso.com. The tenant contains two groups named ResearchReviewersGroup1 and ResearchReviewersGroup2.
Data Environment
Contoso has the following data environment:
- The Sales division uses a Microsoft Power BI Premium capacity.
- The semantic model of the Online Sales department includes a fact table named Orders that uses Import made. In the system of origin, the OrderID value represents the sequence in which orders are created.
- The Research department uses an on-premises, third-party data warehousing product.
- Fabric is enabled for contoso.com.
- An Azure Data Lake Storage Gen2 storage account named storage1 contains Research division data for a product line named Productline1. - The data is in the delta format.
- A Data Lake Storage Gen2 storage account named storage2 contains Research division data for a product line named Productline2. The data is in the CSV format.
Requirements
Planned Changes
Contoso plans to make the following changes:
- Enable support for Fabric in the Power BI Premium capacity used by the Sales division.
- Make all the data for the Sales division and the Research division available in Fabric.
- For the Research division, create two Fabric workspaces named Productline1ws and Productine2ws.
- In Productline1ws, create a lakehouse named Lakehouse1.
- In Lakehouse1, create a shortcut to storage1 named ResearchProduct.
Data Analytics Requirements
Contoso identifies the following data analytics requirements:
- All the workspaces for the Sales division and the Research division must support all Fabric experiences.
- The Research division workspaces must use a dedicated, on-demand capacity that has per- minute billing.
- The Research division workspaces must be grouped together logically to support OneLake data hub filtering based on the department name.
- For the Research division workspaces, the members of ResearchReviewersGroup1 must be able to read lakehouse and warehouse data and shortcuts by using SQL endpoints.
- For the Research division workspaces, the members of ResearchReviewersGroup2 must be able to read lakehouse data by using Lakehouse explorer.
- All the semantic models and reports for the Research division must use version control that supports branching.
Data Preparation Requirements
Contoso identifies the following data preparation requirements:
- The Research division data for Productline1 must be retrieved from Lakehouse1 by using Fabric notebooks.
- All the Research division data in the lakehouses must be presented as managed tables in Lakehouse explorer.
Semantic Model Requirements
Contoso identifies the following requirements for implementing and managing semantic models:
- The number of rows added to the Orders table during refreshes must be minimized.
- The semantic models in the Research division workspaces must use Direct Lake mode.
General Requirements
Contoso identifies the following high-level requirements that must be considered for all solutions:
- Follow the principle of least privilege when applicable.
- Minimize implementation and maintenance effort when possible.
Hotspot Question
You need to migrate the Research division data for Productline1. The solution must meet the data preparation requirements.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Requirements: Use managed tables.
If you use saveAsTable() you don't need to specify the path "Table/"
If you you save() you specify the full path
質問 # 55
You have a Fabric tenant that contains a new semantic model in OneLake.
You use a Fabric notebook to read the data into a Spark DataFrame.
You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.
Solution: You use the following PySpark expression:
df .sumary ()
Does this meet the goal?
- A. No
- B. Yes
正解：B
解説：
Yes, the df.summary() method does meet the goal. This method is used to compute specified statistics for numeric and string columns. By default, it provides statistics such as count, mean, stddev, min, and max.
References = The PySpark API documentation details the summary() function and the statistics it provides.
質問 # 56
You have a Microsoft Power BI semantic model that contains a measure named TotalSalesAmount.
TotalSalesAmount returns a sales revenue amount that is translated into a selected currency.
You need to ensure that the value returned by TotalSalesAmount is formatted to use the correct currency symbol.
What should you include in the solution?
- A. The WINDOW DAX function
- B. A field parameter
- C. A dynamic format string
- D. A linguistic schema
正解：C
質問 # 57
You have a Fabric tenant that contains two workspaces named Workspace1 and Workspace2 and a user named User1.
You need to ensure that User1 can perform the following tasks:
- Create a new domain.
- Create two subdomains named subdomain1 and subdomain2.
- Assign Workspace1 to subdomain1.
- Assign Workspace2 to subdomain2.
The solution must follow the principle of least privilege.
Which role should you assign to User1?
- A. domain contributor
- B. workspace Admin
- C. Fabric admin
- D. domain admin
正解：C
解説：
https://learn.microsoft.com/en-us/fabric/governance/domains#create-a-domain
質問 # 58
You have a Fabric tenant tha1 contains a takehouse named Lakehouse1. Lakehouse1 contains a Delta table named Customer.
When you query Customer, you discover that the query is slow to execute. You suspect that maintenance was NOT performed on the table.
You need to identify whether maintenance tasks were performed on Customer.
Solution: You run the following Spark SQL statement:
EXPLAIN TABLE customer
Does this meet the goal?
- A. Yes
- B. No
正解：B
質問 # 59
......
Microsoft DP-600 認定試験の出題範囲：
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
DP-600問題集と練習テスト（166試験問題)：https://www.goshiken.com/Microsoft/DP-600-mondaishu.html
ガイド（2026年最新）実際のMicrosoft DP-600試験問題：https://drive.google.com/open?id=1n7uiGAHjsMX-6wX3bUZodGHfhsZD4aJz