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The DP-700 exam questions are designed and verified by experienced and qualified DP-700 exam trainers. So you rest assured that with Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) exam dumps you can streamline your DP-700 Exam Preparation process and get confidence to pass Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) exam in first attempt.
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Implementing Data Engineering Solutions Using Microsoft Fabric |
| Exam Number: | DP-700 |
| Passing Score: | 700 (scaled score 100–1000) |
| Exam Format: | Multiple choice, Case studies, Multiple select, Interactive items, Scenario-based |
| Exam Duration: | 100 minutes |
| Exam Price: | $165 USD |
| Available Languages: | Spanish, Korean, Chinese (Simplified), Portuguese (Brazil), English, German, French, Japanese |
| Certificate Validity Period: | 1 year |
| Real Exam Qty: | 50–60 |
| Related Certifications: | Microsoft Certified: Azure Data Engineer Associate Microsoft Certified: Power BI Data Analyst Associate |
| Recommended Training: | Microsoft Fabric Documentation Microsoft Learn: Implementing Data Engineering Solutions Using Microsoft Fabric |
| Exam Registration: | Microsoft Official Exam Registration Pearson VUE Registration |
| Sample Questions: | Microsoft DP-700 Sample Questions |
| Exam Way: | Online proctored or onsite testing center |
| Pre Condition: | No mandatory prerequisites; recommended experience with data integration, transformation, SQL, PySpark, KQL, and Microsoft Fabric |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700 |
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NEW QUESTION # 70
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 # 71
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: A
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 # 72
You have a Fabric workspace that contains a lakehouse named Lakehouse1. a Dataflow Gen2 named Dataflow1, and a pipeline named Pipeline1. Dataflow1 loads data into Lakehouse1.
You need to ensure that Dataflow! always performs a full data load into Lakehouse1. The solution must minimize how long it takes to load the data.
What should you do?
Answer: A
NEW QUESTION # 73
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: B
Explanation:
This code does not meet the goal because it uses order by, which is not valid in KQL. The correct term in KQL is sort by.
Correct code should look like:
NEW QUESTION # 74
You have a Fabric workspace that contains an eventstream named EventStreaml. EventStreaml outputs events to a table named Tablel in a lakehouse. The streaming data is souiced from motorway sensors and represents the speed of cars.
You need to add a transformation to EventStream1 to average the car speeds. The speeds must be grouped by non-overlapping and contiguous time intervals of one minute. Each event must belong to exactly one window.
Which windowing function should you use?
Answer: B
NEW QUESTION # 75
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2026 Latest ValidExam DP-700 PDF Dumps and DP-700 Exam Engine Free Share: https://drive.google.com/open?id=1x4Gz2PCY_v8IhZo__ZDmi6vndQAkputb