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NEW QUESTION # 125
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.
Answer:
Explanation:
Explanation:
NEW QUESTION # 126
You have a Fabric tenant that is linked to a Microsoft Entra tenant. The Microsoft [intra tenant contains a user named User1 and two groups named Group! and Groups.
The Fabric tenant contains the workspaces shown in the following table.
You need to meet the following access requirements:
* User1 must have read access to the following:
* The operations department reports
* The HR department warehouse and reports
* The legal department warehouse and reports
* User1 must be able to create new items in Workspace
* Group1 must have access to the finance department warehouse and reports.
* Group1 must be able to add new users to the finance department workspace.
* Group2 must have access to only the HR warehouse and the legal warehouse.
The solution must follow the principle of least privilege.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 127
You have a Fabric workspace named WS1 that contains several scheduled data pipelines. WS1 has workspace monitoring enabled, and the monitoring eventhouse contains a table named ItemJobEventLogs.
Users report that some downstream reports are missing newly ingested data.
You need to identify failed pipeline runs from the last nine minutes and return only the columns needed for troubleshooting.
How should you complete the KQL query?
Answer:
Explanation:
Explanation:
First selection: JobType == ' Pipeline '
Second selection: SecondsAgo < = 540
Completed KQL query:
ItemJobEventLogs
| where JobType == ' Pipeline ' and JobStatus == ' Failed '
| extend SecondsAgo = datetime_diff( ' second ' , now(), ingestion_time())
| where SecondsAgo < = 540
| order by Timestamp desc
| project Timestamp, ItemName, WorkspaceName, JobStartTime, JobEndTime, JobStatus The correct selections are JobType == ' Pipeline ' and SecondsAgo < = 540 . Microsoft Fabric workspace monitoring writes item-level execution information to the ItemJobEventLogs table in the monitoring Eventhouse. Microsoft provides this specific KQL pattern for detecting recent pipeline failures , using JobType == ' Pipeline ' together with JobStatus == ' Failed ' .
The query then calculates:
datetime_diff( ' second ' , now(), ingestion_time())
This produces the approximate number of seconds elapsed since each monitoring record was ingested.
Because nine minutes = 540 seconds , the predicate SecondsAgo < = 540 retains records ingested during the preceding nine-minute window. SecondsAgo > = 540 would do the opposite by retaining records at least nine minutes old.
JobEndTime > = ago(9m) is not the correct selection because the query explicitly derives ingestion recency through ingestion_time(). Microsoft's documented workspace-monitoring example uses the same SecondsAgo < = 540 pattern.
Finally, project limits the result to the operational fields required for troubleshooting: timestamp, pipeline name, workspace, start/end times, and failure status.
Study Guide reference: Monitor and optimize an analytics solution # workspace monitoring # Eventhouse monitoring logs # KQL analysis of pipeline execution and failures.
NEW QUESTION # 128
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a Fabric eventstream that loads data into a table named Bike_Location in a KQL database. The table contains the following columns:
You need to apply transformation and filter logic to prepare the data for consumption. The solution must return data for a neighbourhood named Sands End when No_Bikes is at least 15. The results must be ordered by No_Bikes in ascending order.
Solution: You use the following code segment:
Does this meet the goal?
Answer: B
Explanation:
Filter Condition: It correctly filters rows where Neighbourhood is "Sands End" and No_Bikes is greater than or equal to 15.
Sorting: The sorting is explicitly done by No_Bikes in ascending order using sort by No_Bikes asc.
Projection: It projects the required columns (BikepointID, Street, Neighbourhood, No_Bikes, No_Empty_Docks, Timestamp), which minimizes the data returned for consumption.
NEW QUESTION # 129
Your company has three newly created data engineering teams named Team1, Team2, and Team3 that plan to use Fabric. The teams have the following personas:
* Team1 consists of members who currently use Microsoft Power BI. The team wants to transform data by using by a low-code approach.
* Team2 consists of members that have a background in Python programming. The team wants to use PySpark code to transform data.
* Team3 consists of members who currently use Azure Data Factory. The team wants to move data between source and sink environments by using the least amount of effort.
You need to recommend tools for the teams based on their current personas.
What should you recommend for each team? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 130
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