Azure Data Factory for Beginners - Build Data Ingestion - Create Source Dataset

The video tutorial guides viewers through creating a data set in Azure Data Factory, starting with linking the data factory to Azure DevOps and creating a new working branch. It then covers configuring a data set for CSV files in Azure BLOB Storage, including adding parameters and validating the setup. The tutorial concludes with a brief overview of the data set properties and next steps for writing data into the data lake.

What is the first step in setting up a dataset in Azure Data Factory?

• Opening the Azure portal

• Creating a new working branch

• Reviewing data

• Linking to Azure DevOps

What is the purpose of creating a new working branch in Git?

• To work on new features separately

• To review data

• To merge changes immediately

• To delete old data

Which storage option is selected for creating a new dataset in Azure Data Factory?

• Azure SQL Database

• Azure BLOB Storage

• Azure Table Storage

• Azure Data Lake

What is the delimiter used in the CSV files for the dataset?

• Pipe

• Comma

• Tab

• Semicolon

What is the final step after adding parameters to the dataset?

• Linking to a new service

• Creating a new branch

• Validating the setup

• Deleting the dataset

What type of file is unexpectedly found alongside the CSV files?

• DOCX

• TXT

• JSON

• XML

What is the default value supplied for the container parameter?

• Operations

• Marketing

• Sales

• Finance