DP-700 examination of the latest Microsoft certification exam questions and answers

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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
Exam Format:Multiple select, Multiple choice, Interactive items, Scenario-based, Case studies
Available Languages:Chinese (Simplified), Korean, Japanese, German, Spanish, Portuguese (Brazil), French, English
Real Exam Qty:50–60
Passing Score:700 (scaled score 100–1000)
Exam Duration:100 minutes
Certificate Validity Period:1 year
Exam Price:$165 USD
Related Certifications:Microsoft Certified: Power BI Data Analyst Associate
Microsoft Certified: Azure Data Engineer Associate
Recommended Training:Microsoft Learn: Implementing Data Engineering Solutions Using Microsoft Fabric
Microsoft Fabric Documentation
Exam Registration:Pearson VUE Registration
Microsoft Official Exam Registration
Sample Questions:Microsoft DP-700 Sample Questions
Exam Way:Online proctored or onsite testing center
Pre Condition:No mandatory prerequisites; recommended experience with data integration, transformation, SQL, PySpark, KQL, and Microsoft Fabric
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700

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The Microsoft DP-700 certification brings multiple career benefits. Reputed firms happily hire you for well-paid jobs when you earn the Implementing Data Engineering Solutions Using Microsoft Fabric. If you are already an employee of a tech company, you get promotions and salary hikes upon getting the DP-700 credential. All these career benefits come when you crack the Microsoft DP-700 certification examination. To pass the DP-700 test, you need to prepare well from updated practice material such as real Microsoft DP-700 Exam Questions.

Microsoft DP-700 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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.

Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q112-Q117):

NEW QUESTION # 112
You have a Fabric workspace that contains a notebook named Notebook1 and an Azure Data Factory pipeline named Pipeline1. Pipeline1 runs Notebook1 by using a notebook activity and passes simple parameter types.
Notebook1 contains the following cells:
Cell 3: Contains %%configure code that sets Apache Spark session properties Cell 5: Contains a designated parameters cell During an execution of Pipeline1, the pipeline fails before any business logic runs.
You need to ensure that Pipeline1 runs successfully.
What should you do?

Answer: B


NEW QUESTION # 113
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 # 114
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:


NEW QUESTION # 115
You have an Azure event hub. Each event contains the following fields:
BikepointID
Street
Neighbourhood
Latitude
Longitude
No_Bikes
No_Empty_Docks
You need to ingest the events. The solution must only retain events that have a Neighbourhood value of Chelsea, and then store the retained events in a Fabric lakehouse.
What should you use?

Answer: B

Explanation:
An eventstream is the best solution for ingesting data from Azure Event Hub into Fabric, while applying filtering logic such as retaining only the events that have a Neighbourhood value of "Chelsea." Eventstreams in Microsoft Fabric are designed for handling real-time data streams and can apply transformation logic directly on incoming events. In this case, the eventstream can filter events based on the Neighbourhood field before storing the retained events in a Fabric lakehouse.
Eventstreams are well-suited for stream processing, such as this case where you need to filter out only specific data (events with a Neighbourhood of "Chelsea") before storing it in the lakehouse.


NEW QUESTION # 116
You have a Fabric workspace that contains an eventstream named Eventstream1. Eventstream1 processes data from a thermal sensor by using event stream processing, and then stores the data in a lakehouse.
You need to modify Eventstream1 to include the standard deviation of the temperature.
Which transform operator should you include in the Eventstream1 logic?

Answer: B

Explanation:
To compute the standard deviation of the temperature from the thermal sensor data, you would use the Aggregate transform operator in Eventstream1. The Aggregate operator allows you to apply functions like sum, average, count, and statistical functions like standard deviation across a group of rows or events. This operator is ideal for operations that require summarizing or computing statistics over a dataset, such as calculating the standard deviation.


NEW QUESTION # 117
......

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