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Microsoft DP-700 Exam Syllabus Topics:

Topic
Details

Topic 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.

Topic 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.

Topic 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 Examinations Actual Questions <<

DP-700 Examinations Actual Questions - Pass Guaranteed Quiz DP-700 - Implementing Data Engineering Solutions Using Microsoft Fabric First-grade Vce Download

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q72-Q77):

NEW QUESTION # 72
You have the development groups shown in the following table.

You have the projects shown in the following table.

You need to recommend which Fabric item to use based on each development group's skillset The solution must meet the project requirements and minimize development effort What should you recommend for each group? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

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?

A. no
B. Yes

Answer: A

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 a warehouse named DW1. DW1 contains the following tables and columns.

You need to create an output that presents the summarized values of all the order quantities by year and product. The results must include a summary of the order quantities at the year level for all the products.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 75
HOTSPOT
You have a Fabric workspace that contains a warehouse named DW1. DW1 contains the following tables and columns.

Answer:

Explanation:

NEW QUESTION # 76
You need to recommend a solution to resolve the MAR1 connectivity issues. The solution must minimize development effort. What should you recommend?

A. Add a ForEach activity to the data pipeline.
B. Call a notebook from the data pipeline.
C. Configure Fault tolerance for the Copy data activity.
D. Configure retries for the Copy data activity.

Answer: D

NEW QUESTION # 77
......

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Caleb Johnson Caleb Johnson

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