DP-700認證 & DP-700考試資訊

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Microsoft DP-700 考試大綱：

主題簡介
主題 1
  • Ingest and transform data: This section of the exam measures the skills of Data Engineers that cover designing and implementing data loading patterns. It emphasizes preparing data for loading into dimensional models, handling batch and streaming data ingestion, and transforming data using various methods. A skill to be measured is applying appropriate transformation techniques to ensure data quality.
主題 2
  • Monitor and optimize an analytics solution: This section of the exam measures the skills of Data Analysts in monitoring various components of analytics solutions in Microsoft Fabric. It focuses on tracking data ingestion, transformation processes, and semantic model refreshes while configuring alerts for error resolution. One skill to be measured is identifying performance bottlenecks in analytics workflows.
主題 3
  • Implement and manage an analytics solution: This section of the exam measures the skills of Microsoft Data Analysts regarding configuring various workspace settings in Microsoft Fabric. It focuses on setting up Microsoft Fabric workspaces, including Spark and domain workspace configurations, as well as implementing lifecycle management and version control. One skill to be measured is creating deployment pipelines for analytics solutions.

>> DP-700認證 <<

Microsoft DP-700認證：Implementing Data Engineering Solutions Using Microsoft Fabric考試—100％免費

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最新的 Microsoft Certified: Fabric Data Engineer Associate DP-700 免費考試真題 (Q45-Q50):

問題 #45
You have a Fabric workspace that contains a warehouse named Warehouse1. Data is loaded daily into Warehouse1 by using data pipelines and stored procedures.
You discover that the daily data load takes longer than expected.
You need to monitor Warehouse1 to identify the names of users that are actively running queries.
Which view should you use?

答案：B

解題說明：
sys.dm_exec_sessions provides real-time information about all active sessions, including the user, session ID, and status of the session. You can filter on session status to see users actively running queries.


問題 #46
You have a Fabric warehouse named DW1 that contains four staging tables named ProductCategory, ProductSubcategory, Product, and SalesOrder. ProductCategory, ProductSubcategory, and Product are used often in analytical queries.
You need to implement a star schema for DW1. The solution must minimize development effort.
Which design approach should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

答案：

解題說明：

Explanation:


問題 #47
You have a Fabric workspace that contains an eventhouse and a KQL database named Database1. Database1 has the following:
A table named Table1
A table named Table2
An update policy named Policy1
Policy1 sends data from Table1 to Table2.
The following is a sample of the data in Table2.

Recently, the following actions were performed on Table1:
An additional element named temperature was added to the StreamData column.
The data type of the Timestamp column was changed to date.
The data type of the DeviceId column was changed to string.
You plan to load additional records to Table2.
Which two records will load from Table1 to Table2? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

答案：A,D

解題說明：
Changes to Table1 Structure:
StreamData column: An additional temperature element was added.
Timestamp column: Data type changed from datetime to date.
DeviceId column: Data type changed from guid to string.
Impact of Changes:
Only records that comply with Table2's structure will load.
Records that deviate from Table2's column data types or structure will be rejected.
Record B:
Timestamp: Matches Table2 (datetime format).
DeviceId: Matches Table2 (guid format).
StreamData: Contains only the index and eventid, which matches Table2.
Accepted because it fully matches Table2's structure and data types.
Record D:
Timestamp: Matches Table2 (datetime format).
DeviceId: Matches Table2 (guid format).
StreamData: Matches Table2's structure.
Accepted because it fully matches Table2's structure and data types.


問題 #48
You have Fabric workspace that contains eventhouse named Eventhouse1.
In Eventhouse1, you plan to create a table named EventStreamData in a KQL database. The table will contain data based on the following sample.

答案：

解題說明：

Explanation:


問題 #49
HOTSPOT
You need to troubleshoot the ad-hoc query issue.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

答案：

解題說明：

Explanation:
A screenshot of a computer Description automatically generated

SELECT last_run_start_time, last_run_command: These fields will help identify the execution details of the long-running queries.
FROM queryinsights.long_running_queries: The correct solution is to check the long-running queries using the queryinsights.long_running_queries view, which provides insights into queries that take longer than expected to execute.
WHERE last_run_total_elapsed_time_ms > 7200000: This condition filters queries that took more than 2 hours to complete (7200000 milliseconds), which is relevant to the issue described.
AND number_of_failed_runs > 1: This condition is key for identifying queries that have failed more than once, helping to isolate the problematic queries that cause failures and need attention.


問題 #50
......

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