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>> Microsoft DP-700 Certification Dumps <<
Getting the Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) certification exam is necessary in order to get a job in your desired tech company. Success in the Implementing Data Engineering Solutions Using Microsoft Fabric certification exam gives you an edge over the others because you will have certified skills. The Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) certification exam badge will make a good impression on the interviewer. Most of the people planning to attempt the Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) exam are confused that how will they prepare and pass Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) exam with good grades.
NEW QUESTION # 54
You need to develop an orchestration solution in fabric that will load each item one after the other. The solution must be scheduled to run every 15 minutes. Which type of item should you use?
Answer: C
NEW QUESTION # 55
DRAG DROP
You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiData.
The following is a sample of the data in TaxiData.
You need to build two KQL queries. The solution must meet the following requirements:
One of the queries must partition RunningTotalAmount by VendorID.
The other query must create a column named FirstPickupDateTime that shows the first value of each hour from tpep_pickup_datetime partitioned by payment_type.
How should you complete each query? To answer, drag the appropriate values 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.
Answer:
Explanation:
Explanation:
Partition the RunningTotalAmount by VendorID. - Row_cumsum
The Row_cumsum function computes the cumulative sum of a column while optionally restarting the accumulation based on a condition. In this case, it calculates the cumulative sum of total_amount for each VendorID, restarting when the VendorID changes (VendorID != prev(VendorID)).
Create a column FirstPickupDateTime that shows the first value of each hour from tpep_pickup_datetime, partitioned by payment_type - Row_window_session
NEW QUESTION # 56
You have a Fabric workspace that contains a semantic model named Model1.
You need to dynamically execute and monitor the refresh progress of Model1.
What should you use?
Answer: D
NEW QUESTION # 57
You have a Fabric workspace that contains a semantic model named Model1.
You need to dynamically execute and monitor the refresh progress of Model1.
What should you use?
Answer: D
Explanation:
Semantic models in Microsoft Fabric are part of Power BI datasets and require refreshes to stay updated with the latest data.
Dynamically executing and monitoring the refresh progress requires a tool or approach that integrates with Fabric's capabilities for semantic models.
NEW QUESTION # 58
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:
BikepointID
Street
Neighbourhood
No_Bikes
No_Empty_Docks
Timestamp
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: A
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 # 59
......
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