CompTIA
Checkpoint
ISC
HP
Dell
EC-Council
EXIN
Fortinet
ITIL®
Juniper
PMI
Microsoft
VMware
Avaya
Google
Salesforce
Amazon
Palo Alto Networks
Certiport
ISC2
All Vendors
  2. Home
  3. Exams
  4. Microsoft
  5. DP-600

Free DP-600 Exam Braindumps (page: 15)

Page 14 of 36
PDF with 183 Questions

HOTSPOT (Drag and Drop is not supported)
You have a Microsoft Power BI report and a semantic model that uses Direct Lake mode.
From Power BI Desktop, you open Performance analyzer as shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

  1. See Explanation section for answer.

Answer(s): A

Explanation:



HOTSPOT (Drag and Drop is not supported)
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a table named Nyctaxi_raw. Nyctaxi_row contains the following table:
You create a Fabric notebook and attach it to Lakehouse1.
You need to use PySpark code to transform the data. The solution must meet the following requirements:
Add a column named pickupDate that will contain only the date portion of pickupDateTime.
Filter the DataFrame to include only rows where fareAmount is a positive number that is less than 100.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

  1. See Explanation section for answer.

Answer(s): A

Explanation:



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 tenant that contains a new semantic model in OneLake.
You use a Fabric notebook to read the data into a Spark DataFrame.
You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.
Solution: You use the following PySpark expression:
df.explain()
Does this meet the goal?

  1. Yes
  2. No

Answer(s): B



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 tenant that contains a new semantic model in OneLake.
You use a Fabric notebook to read the data into a Spark DataFrame.
You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.
Solution: You use the following PySpark expression:
df.show()
Does this meet the goal?

  1. Yes
  2. No

Answer(s): B






Post your Comments and Discuss Microsoft DP-600 exam with other Community members:

DP-600 Exam Discussions & Posts