DP-203 Exam Question 11

You configure version control for an Azure Data Factory instance 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.

DP-203 Exam Question 12

You have an Azure Synapse serverless SQL pool.
You need to read JSON documents from a file by using the OPENROWSET function.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

DP-203 Exam Question 13

From a website analytics system, you receive data extracts about user interactions such as downloads, link clicks, form submissions, and video plays.
The data contains the following columns.

You need to design a star schema to support analytical queries of the data. The star schema will contain four tables including a date dimension.
To which table should you add each column? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

DP-203 Exam Question 14

You have an Azure subscription.
You plan to build a data warehouse in an Azure Synapse Analytics dedicated SQL pool named pool1 that will contain staging tables and a dimensional model. Pool1 will contain the following tables.

You need to design the table storage for pool1. The solution must meet the following requirements:
Maximize the performance of data loading operations to Staging.WebSessions.
Minimize query times for reporting queries against the dimensional model.
Which type of table distribution should you use for each table? To answer, drag the appropriate table distribution types to the correct tables. Each table distribution type 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.

DP-203 Exam Question 15

You are creating an Apache Spark job in Azure Databricks that will ingest JSON-formatted data.
You need to convert a nested JSON string into a DataFrame that will contain multiple rows.
Which Spark SQL function should you use?