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| Section | Weight | Objectives |
|---|---|---|
| Ingest and transform data | 30-35% | - Ingest data using Data Factory pipelines and Dataflows Gen2 - Ingest and transform data using eventstreams - Design and implement loading patterns - Transform data using Dataflows Gen2 and notebooks - Optimize and manage Delta tables |
| Implement and manage an analytics solution | 30-35% | - Configure and manage workspace settings and item access - Implement security and governance - Implement lifecycle management and source control for analytics assets - Orchestrate processes with Data Factory pipelines |
| Monitor and optimize an analytics solution | 30-35% | - Optimize performance of data storage and queries - Monitor Fabric items - Implement error handling in pipelines |
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NEW QUESTION # 62
You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse2. A team of data analysts has Viewer role access to Workspace1. You create a table by running the following statement.
You need to ensure that the team can view only the first two characters and the last four characters of the Creditcard attribute.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 63
You have a Fabric workspace named Workspace1.
You enable workspace monitoring for Workspace1.
You need to return records ingested during the last 540 seconds.
Which KQL filter should you use?
Answer: A
Explanation:
The correct answer is C because the requirement is specifically to identify records based on when they were ingested into the Fabric monitoring data store , rather than when a monitored job started or ended.
In KQL, ingestion_time() returns the approximate UTC datetime at which the current record was ingested and became available for querying. The datetime_diff() function uses the syntax datetime_diff(period, datetime1, datetime2) and effectively calculates the difference between datetime1 and datetime2. Therefore:
datetime_diff( ' second ' , now(), ingestion_time())
calculates how many seconds have elapsed between the record ' s ingestion time and the current time.
Filtering for values < = 540 returns records ingested within approximately the previous nine minutes.
Microsoft explicitly uses this same expression in Fabric workspace-monitoring examples for retrieving recent records. ( Microsoft Learn ) Options A and B evaluate job execution timestamps rather than ingestion recency. Option D reverses the datetime operands, which normally produces a negative elapsed-time value and therefore does not correctly represent " seconds ago. " Study Guide reference: Monitor and optimize an analytics solution # monitor Fabric workloads, workspace monitoring, KQL querying, and operational log analysis. ( Microsoft Learn )
NEW QUESTION # 64
HOTSPOT
You have a Fabric workspace that contains two lakehouses named Lakehouse1 and Lakehouse2. Lakehouse1 contains staging data in a Delta table named Orderlines. Lakehouse2 contains a Type 2 slowly changing dimension (SCD) dimension table named Dim_Customer.
You need to build a query that will combine data from Orderlines and Dim_Customer to create a new fact table named Fact_Orders. The new table must meet the following requirements:
Enable the analysis of customer orders based on historical attributes.
Enable the analysis of customer orders based on the current attributes.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 65
You have a Fabric workspace that contains a warehouse named Warehouse!. Warehousel contains a table named DimCustomers. DimCustomers contains the following columns:
* CustomerName
* CustomerlD
* BirthDate
* Email
You need to configure security to meet the following requirements:
* BirthDate in DimCustomer must be masked and display 1900-01-01.
* Email in DimCustomer must be masked and display only the first leading character and the last five characters.
How should you complete the statement? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 66
Exhibit.
You have a Fabric workspace that contains a write-intensive warehouse named DW1. DW1 stores staging tables that are used to load a dimensional model. The tables are often read once, dropped, and then recreated to process new data.
You need to minimize the load time of DW1.
What should you do?
Answer: B
NEW QUESTION # 67
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