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Microsoft DP-700 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Implementing Data Engineering Solutions Using Microsoft Fabric
Exam Number:DP-700
Certificate Validity Period:1 year (renewable)
Real Exam Qty:40-60
Passing Score:700/1000
Exam Price:Varies by region (approx. $165 USD)
Available Languages:Japanese, Simplified Chinese, French, Korean, Spanish, English, German, Portuguese (Brazil)
Exam Format:Multiple response, Scenario-based questions, Case studies, Multiple choice
Related Certifications:Microsoft Certified: Azure Data Engineer Associate
Microsoft Certified: Fabric Analytics Engineer Associate
Exam Duration:100-120
Recommended Training:Microsoft Fabric Documentation
Microsoft Learn DP-700 Learning Path
Exam Registration:Microsoft Learn Certification Exam Page
Pearson VUE Microsoft Exams
Sample Questions:Microsoft DP-700 Sample Questions
Exam Way:Online proctored via Pearson VUE or in-person at authorized testing centers
Pre Condition:No formal prerequisites, but recommended experience with Azure data services and basic data engineering concepts
Official Syllabus URL:https://learn.microsoft.com/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
  • 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.

Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q71-Q76):

NEW QUESTION # 71
You need to recommend a Fabric streaming solution that will use the sources shown in the following table.

The solution must minimize development effort.
What should you include in the recommendation for each source? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 72
You have a Fabric workspace that contains a warehouse named Warehouse!. Warehousel contains a table named DimCustomers. DimCustomers contains the following columns:
* CustomerName
* CustomerlD
* BirthDate
* Email
You need to configure security to meet the following requirements:
* BirthDate in DimCustomer must be masked and display 1900-01-01.
* Email in DimCustomer must be masked and display only the first leading character and the last five characters.
How should you complete the statement? To answer, select the appropriate options in the answer are a. NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 73
You have a Fabric warehouse named DW1 that loads data by using a data pipeline named Pipeline1. Pipeline1 uses a Copy data activity with a dynamic SQL source. Pipeline1 is scheduled to run every 15 minutes.
You discover that Pipeline1 keeps failing.
You need to identify which SQL query was executed when the pipeline failed.
What should you do?

Answer: C

Explanation:
The input JSON contains the configuration details and parameters passed to the Copy data activity during execution, including the dynamically generated SQL query.
Viewing the input JSON for the failed pipeline run provides direct insight into what query was executed at the time of failure.


NEW QUESTION # 74
You have a Fabric workspace named WS1 that has the following configurations:
Contains a custom Apache Spark pool named PoolA that is the default pool Contains a custom environment named Env1 that is the default environment Has Customize compute configurations for items set to Off Has high concurrency mode enabled WS1 contains a notebook named Notebook1 that is attached to Env1. The first cell in Notebook1 contains the following text.
%pip install
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 75
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:
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:
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 # 76
......

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