Azure Data Factory for Beginners - Build Data Ingestion - Read from Azure Storage Plan

The video tutorial explains the steps to set up a data factory pipeline that reads files from an Azure BLOB storage account, specifically focusing on the finance container. It covers creating the finance container, uploading necessary CSV and JSON files, and setting up a data set within the data factory to view the container's contents. The tutorial concludes with a brief wrap-up and a transition to the next lecture.

What is the primary function of the data factory pipeline as discussed in the first section?

• To delete files from the Azure BLOB storage account

• To read files from the Azure BLOB storage account

• To update the Azure BLOB storage account

• To create a new Azure account

What is the first step in setting up the data factory pipeline?

• Creating a finance container

• Deleting old files

• Uploading files

• Creating a dataset

Which types of files are uploaded to the finance container?

• Image and Video files

• PDF and Word files

• CSV and JSON files

• Text and Excel files

What is the purpose of creating a dataset in the data factory?

• To view the contents of the container and directory

• To delete the container

• To modify the files in the container

• To create new files in the container

Why is metadata important in the dataset creation process?

• It helps in deleting files

• It provides a list of files as metadata

• It compresses the files

• It encrypts the files