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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
Real Exam Qty:40-60
Passing Score:700/1000
Related Certifications:Microsoft Certified: Azure Data Engineer Associate
Microsoft Certified: Fabric Analytics Engineer Associate
Certificate Validity Period:1 year (renewable)
Exam Price:Varies by region (approx. $165 USD)
Available Languages:Japanese, English, Korean, Simplified Chinese, German, Spanish, Portuguese (Brazil), French
Exam Format:Case studies, Multiple choice, Scenario-based questions, Multiple response
Exam Duration:100-120
Recommended Training:Microsoft Fabric Documentation
Microsoft Learn DP-700 Learning Path
Exam Registration:Pearson VUE Microsoft Exams
Microsoft Learn Certification Exam Page
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
  • 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 2
  • 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 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 (Q12-Q17):

NEW QUESTION # 12
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 # 13
What should you do to optimize the query experience for the business users?

Answer: B


NEW QUESTION # 14
You plan to process the following three datasets by using Fabric:
* Dataset1: This dataset will be added to Fabric and will have a unique primary key between the source and the destination. The unique primary key will be an integer and will start from 1 and have an increment of 1.
* Dataset2: This dataset contains semi-structured data that uses bulk data transfer. The dataset must be handled in one process between the source and the destination. The data transformation process will include the use of custom visuals to understand and work with the dataset in development mode.
* Dataset3. This dataset is in a takehouse. The data will be bulk loaded. The data transformation process will include row-based windowing functions during the loading process.
You need to identify which type of item to use for the datasets. The solution must minimize development effort and use built-in functionality, when possible. What should you identify for each dataset? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 15
You are implementing the following data entities in a Fabric environment:
Entity1: Available in a lakehouse and contains data that will be used as a core organization entity Entity2: Available in a semantic model and contains data that meets organizational standards Entity3: Available in a Microsoft Power BI report and contains data that is ready for sharing and reuse Entity4: Available in a Power BI dashboard and contains approved data for executive-level decision making Your company requires that specific governance processes be implemented for the data.
You need to apply endorsement badges to the entities based on each entity's use case.
Which badge should you apply to each entity? To answer, drag the appropriate badges the correct entities.
Each badge 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:


NEW QUESTION # 16
Your company has a team of developers. The team creates Python libraries of reusable code that is used to transform data.
You create a Fabric workspace name Workspace1 that will be used to develop extract, transform, and load (ETL) solutions by using notebooks.
You need to ensure that the libraries are available by default to new notebooks in Workspace1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:


NEW QUESTION # 17
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