Authentic Microsoft DP-700 Exam Questions

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Each format has a pool of Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) actual questions which have been compiled under the guidance of thousands of professionals worldwide. Questions in this product will appear in the Microsoft DP-700 final test. Hence, memorizing them will help you get prepared for the DP-700 examination in a short time. The product of BraindumpsVCE comes in PDF, desktop practice exam software, and DP-700 web-based practice test. To give you a complete understanding of these formats, we have discussed their features below.

Microsoft DP-700 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Implementing Data Engineering Solutions Using Microsoft Fabric
Exam Number:DP-700
Exam Duration:100 minutes
Real Exam Qty:50 - 60
Certificate Validity Period:12 Months (Renewable annually)
Available Languages:French, English, Spanish, Simplified Chinese, Japanese, German, Portuguese (Brazil)
Exam Format:Multiple choice, Drag-and-drop, Scenario-based, Case studies
Passing Score:700 / 1000
Related Certifications:Microsoft Certified: Fabric Data Engineer Associate
Exam Price:$165 USD
Sample Questions:Microsoft DP-700 Sample Questions
Exam Way:Online proctored or Test center
Pre Condition:No specific prior certification required.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/dp-700/

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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.

Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q29-Q34):

NEW QUESTION # 29
You need to schedule the population of the medallion layers to meet the technical requirements.
What should you do?

Answer: B

Explanation:
The technical requirements specify that:
Medallion layers must be fully populated sequentially (bronze # silver # gold). Each layer must be populated before the next.
If any step fails, the process must notify the data engineers.
Data imports should run simultaneously when possible.
Why Use a Data Pipeline That Calls Other Data Pipelines?
A data pipeline provides a modular and reusable approach to orchestrating the sequential population of medallion layers.
By calling other pipelines, each pipeline can focus on populating a specific layer (bronze, silver, or gold), simplifying development and maintenance.
A parent pipeline can handle:
- Sequential execution of child pipelines.
- Error handling to send email notifications upon failures.
- Parallel execution of tasks where possible (e.g., simultaneous imports into the bronze layer).


NEW QUESTION # 30
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 this is an SQL-like query and cannot be executed in KQL, which is required for the database.
Correct code should look like:


NEW QUESTION # 31
You have a Fabric workspace.
You are debugging a statement and discover the following issues:
You need to resolve the issues. The solution must ensure that the data types of the results are retained. The results can contain blank cells.
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:


NEW QUESTION # 32
HOTSPOT
You have an Azure Event Hubs data source that contains weather data.
You ingest the data from the data source by using an eventstream named Eventstream1. Eventstream1 uses a lakehouse as the destination.
You need to batch ingest only rows from the data source where the City attribute has a value of Kansas. The filter must be added before the destination. The solution must minimize development effort.
What should you use for the data processor and filtering? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 33
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 KQL database that contains two tables named Stream and Reference. Stream contains streaming data in the following format.

Reference contains reference data in the following format.

Both tables contain millions of rows.
You have the following KQL queryset.

You need to reduce how long it takes to run the KQL queryset.
Solution: You change project to extend.
Does this meet the goal?

Answer: A

Explanation:
Using extend retains all columns in the table, potentially increasing the size of the output unnecessarily.
project is more efficient because it selects only the required columns.


NEW QUESTION # 34
......

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