DP-700試験問題集、DP-700試験過去問

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Microsoft DP-700 Exam Syllabus Topics:

SectionWeightObjectives
Monitor and optimize an analytics solution30-35%- Optimize performance of data storage and queries
- Monitor Fabric items
- Implement error handling in pipelines
Implement and manage an analytics solution30-35%- Implement lifecycle management and source control for analytics assets
- Implement security and governance
- Configure and manage workspace settings and item access
- Orchestrate processes with Data Factory pipelines
Ingest and transform data30-35%- Ingest data using Data Factory pipelines and Dataflows Gen2
- Optimize and manage Delta tables
- Design and implement loading patterns
- Transform data using Dataflows Gen2 and notebooks
- Ingest and transform data using eventstreams

>> DP-700試験問題集 <<

実用的なDP-700|権威のあるDP-700試験問題集試験|試験の準備方法Implementing Data Engineering Solutions Using Microsoft Fabric試験過去問

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric 認定 DP-700 試験問題 (Q67-Q72):

質問 # 67
You have a Fabric workspace named Workspace1 that contains a warehouse named DW1 and a data pipeline named Pipeline1.
You plan to add a user named User3 to Workspace1.
You need to ensure that User3 can perform the following actions:
View all the items in Workspace1.
Update the tables in DW1.
The solution must follow the principle of least privilege.
You already assigned the appropriate object-level permissions to DW1.
Which workspace role should you assign to User3?

正解:D

解説:
To ensure User3 can view all items in Workspace1 and update the tables in DW1, the most appropriate workspace role to assign is the Contributor role. This role allows User3 to:
View all items in Workspace1: The Contributor role provides the ability to view all objects within the workspace, such as data pipelines, warehouses, and other resources.
Update the tables in DW1: The Contributor role allows User3 to modify or update resources within the workspace, including the tables in DW1, assuming that appropriate object-level permissions are set for the warehouse.
This role adheres to the principle of least privilege, as it provides the necessary permissions without granting broader administrative rights.


質問 # 68
HOTSPOT
You are processing streaming data from an external data provider.
You have the following code segment.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

正解:

解説:

Explanation:

Litware from New York will be displayed at the top of the result set - Yes The data is sorted first by Location in descending order and then by UnitsSold in descending order. Since
"New York" is alphabetically the last Location, it will appear first in the result set. Within "New York", Litware has the highest UnitsSold (1000), so it will be displayed at the top.
Fabrikam in Seattle will have value = 2 in the Rank column - No
The row_rank_dense function assigns dense ranks based on UnitsSold within each location. In "Seattle":
Contoso has UnitsSold = 300 # Rank 1
Litware has UnitsSold = 100 # Rank 2
Fabrikam also has UnitsSold = 100, so it shares the same rank (2) as Litware.
Litware in San Francisco will have the same value in the Rank column as Litware in New York - No The rank is calculated separately for each location. In "San Francisco":
Both Relecloud and Litware have UnitsSold = 500, so they share the same rank (1).
In "New York", Litware has the highest UnitsSold = 1000 # Rank 1.
Since ranks are calculated independently for each location, Litware in San Francisco does not share the same rank as Litware in New York.


質問 # 69
You have a Fabric workspace.
You have semi-structured data.
You need to read the data by using T-SQL, KQL, and Apache Spark. The data will only be written by using Spark.
What should you use to store the data?

正解:C

解説:
A lakehouse is the best option for storing semi-structured data when you need to read it using T-SQL, KQL, and Apache Spark. A lakehouse combines the flexibility of a data lake (which can handle semi-structured and unstructured data) with the performance features of a data warehouse. It allows data to be written using Apache Spark and can be queried using different technologies such as T-SQL (for SQL-based querying), KQL (Kusto Query Language for querying), and Apache Spark (for distributed processing). This solution is ideal when dealing with semi-structured data and requiring a versatile querying approach.


質問 # 70
HOTSPOT
You have a Fabric workspace that contains a warehouse named Warehouse1. Warehouse1 contains the following tables and columns.

You need to denormalize the tables and include the ContractType and StartDate columns in the Employee table. The solution must meet the following requirements:
Ensure that the StartDate column is of the date data type.
Ensure that all the rows from the Employee table are preserved and include any matching rows from the Contract table.
Ensure that the result set displays 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 # 71
You have three users named User1, User2, and User3.
You have the Fabric workspaces shown in the following table.

You have a security group named Group1 that contains User1 and User3.
The Fabric admin creates the domains shown in the following table.

User1 creates a new workspace named Workspace3.
You add Group1 to the default domain of Domain1.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

正解:

解説:

Explanation:


質問 # 72
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