Microsoft Fabric Data Engineer (DP-700) - Microsoft Exam Questions

HOTSPOT Your company has three newly created data engineering teams named Team1, Team2, and Team3 that plan to use Fabric. The teams have the following personas:

• Team1 consists of members who currently use Microsoft Power BI. The team wants to transform
data by using by a low-code approach.

• Team2 consists of members that have a background in Python programming. The team wants to
use PySpark code to transform data.

• Team3 consists of members who currently use Azure Data Factory. The team wants to move data
between source and sink environments by using the least amount of effort. You need to recommend tools for the teams based on their current personas. What should you recommend for each team? To answer, select the appropriate options in the answer

NOTE: Each correct selection is worth one point.



area.

HOTSPOT 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

NOTE: Each correct selection is worth one point. options in the answer area.

You have a Google Cloud Storage (GCS) container named storage1 that contains the files shown in



You have a Fabric workspace named Workspace1 that has the cache for shortcuts enabled. the following table. Workspace1 contains a lakehouse named Lakehouse1. Lakehouse1 has the shortcuts shown in the



following table. You need to read data from all the shortcuts. Which shortcuts will retrieve data from the cache?

You need to resolve the sales data issue. The solution must minimize the amount of data transferred.

What should you do?

• Key
You have a Fabric workspace that contains a lakehouse named Lakehousel. Lakehousel contains a HOTSPOT table named Status_Target that has the following columns:

• LastModified

• Status
The data source contains a table named Status.Source that has the same columns as Status_Target. Status.Source is used to populate Status_Target. In a notebook name Notebook!, you load Status_Source to a DataFrame named sourceDF and Status_Target to a DataFrame named targetDF. You need to implement an incremental loading pattern by using Notebook-!. The solution must meet the following requirements:

• For all the matching records that have the same value of key, update the value of LastModified in
Status_Target to the value of LastModified in Status_Source.

• Insert all the records that exist in Status_Source that do NOT exist in Status_Target.

• Set the value of Status in Status_Target to inactive for all the records that were last modified more
than seven days ago and that do NOT exist in Status.Source. How should you complete the statement? To answer, select the appropriate options in the answer

NOTE: Each correct selection is worth one point.



area.