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Microsoft DP-700 Exam Syllabus Topics:

TopicDetails
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
  • 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.
Topic 3
  • 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.

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Hot Microsoft DP-700 Questions - DP-700 Exam Experience

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q93-Q98):

NEW QUESTION # 93
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 # 94
You need to ensure that the data engineers are notified if any step in populating the lakehouses fails. The solution must meet the technical requirements and minimize development effort.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 95
You have a Fabric workspace that contains an eventhouse and a KQL database named Database1. Database1 has the following:
Policy1 sends data from Table1 to Table2.
The following is a sample of the data in Table2.

Recently, the following actions were performed on Table1:
You plan to load additional records to Table2.
Which two records will load from Table1 to Table2? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

Answer: A,D

Explanation:
Changes to Table1 Structure:
Impact of Changes:
Record B:
Accepted because it fully matches Table2's structure and data types.
Record D:
Accepted because it fully matches Table2's structure and data types.


NEW QUESTION # 96
You have a Fabric warehouse named Warehouse1 that contains a table named Table1. Table 1 has a column named EmailAddress. All users have access to Warehouse1.
You need to configure dynamic data masking for the EmailAddress column. The solution must meet the following requirements:
* The solution must NOT change the data in Warehouse1.
* The solution must NOT require changes to the queries that access Table1.
* The solution must NOT require changes to the security or permissions granted to Warehouse1.
What should you use?

Answer: D


NEW QUESTION # 97
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:
This code does not meet the goal because it uses sort by without specifying the order, which defaults to ascending, but explicitly mentioning asc improves clarity.
Correct code should look like:


NEW QUESTION # 98
......

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