Hotspot Question
You have a Fabric tenant that contains a PySpark notebook named Notebook1.
You define sas_token as a variable in the first cell of Notebook1 and store a shared access signature (SAS) token in the variable.
In the second cell, you run the following code.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Correct Answer:

Comment: *

Name: *

Email: *

Verification: *

You have a Fabric tenant that contains a lakehouse.
You are using a Fabric notebook to save a large DataFrame by using the following code.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:
* The results will form a hierarchy of folders for each partition key. - Yes
* The resulting file partitions can be read in parallel across multiple nodes. - Yes
* The resulting file partitions will use file compression. - No
Partitioning data by columns such as year, month, and day, as shown in the DataFrame write operation, organizes the output into a directory hierarchy that reflects the partitioning structure. This organization can improve the performance of read operations, as queries that filter by the partitioned columns can scan only the relevant directories. Moreover, partitioning facilitates parallelism because each partition can be processed independently across different nodes in a distributed system like Spark. However, the code snippet provided does not explicitly specify that file compression should be used, so we cannot assume that the output will be compressed without additional context.
References =
* DataFrame write partitionBy
* Apache Spark optimization with partitioning

Comment: *

Name: *

Email: *

Verification: *

You need to recommend which type of fabric capacity SKU meets the data analytics requirements for the Research division.
What should you recommend?

• A.F
• B.EM
• C.A
• D.P

Comment: *

Name: *

Email: *

Verification: *

You have a Fabric workspace named Workspace 1 that contains a dataflow named Dataflow1. Dataflow1 has a query that returns 2.000 rows. You view the query in Power Query as shown in the following exhibit.

What can you identify about the pickupLongitude column?

• A.The column has duplicate values.
• B.All the table rows are profiled.
• C.The column has missing values.
• D.There are 935 values that occur only once.

Comment: *

Name: *

Email: *

Verification: *

You have source data in a folder on a local computer.
You need to create a solution that will use Fabric to populate a data store. The solution must meet the following requirements:
* Support the use of dataflows to load and append data to the data store.
* Ensure that Delta tables are V-Order optimized and compacted automatically.
Which type of data store should you use?

• A.a KQL database
• B.a lakehouse
• C.a warehouse
• D.an Azure SQL database

Comment: *

Name: *

Email: *

Verification: *