You have an Azure subscription that contains an Azure Synapse Analytics workspace named workspace1. Workspace1 connects to an Azure DevOps repository named repo1. Repo1 contains a collaboration branch named main and a development branch named branch1. Branch1 contains an Azure Synapse pipeline named pipeline1.
In workspace1, you complete testing of pipeline1.
You need to schedule pipeline1 to run daily at 6 AM.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
You have Azure Data Factory configured with Azure Repos Git integration. The collaboration branch and the publish branch are set to the default values.
You have a pipeline named pipeline 1.
You build a new version of pipeline1 in a branch named feature 1.
From the Data Factory Studio, you select Publish
The source code of which branch will be built, and which branch will contain the output of the Azure Resource Manager (ARM) template? To answer, select the appropriate options in the answer area.
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.
A company plans to use Platform-as-a-Service (PaaS) to create the new data pipeline process. The process must meet the following requirements:
Ingest:
Access multiple data sources.
Provide the ability to orchestrate workflow.
Provide the capability to run SQL Server Integration Services packages.
Store:
Optimize storage for big data workloads.
Provide encryption of data at rest.
Operate with no size limits.
Prepare and Train:
Provide a fully-managed and interactive workspace for exploration and visualization.
Provide the ability to program in R, SQL, Python, Scala, and Java.
Provide seamless user authentication with Azure Active Directory.
Model & Serve:
Implement native columnar storage.
Support for the SQL language
Provide support for structured streaming.
You need to build the data integration pipeline.
Which technologies should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
TESTED 21 Nov 2024
