Azure Data Factory for Beginners - Build Data Ingestion - Data Factory Pipeline Plan

The video tutorial explains the setup of a data factory pipeline, starting with reading data from Azure BLOB storage. It discusses the need for parameters to identify the source container and file type, specifically CSV. The tutorial covers reading metadata from a finance container to determine file details, such as the last modified date, for filtering purposes. The final steps involve processing and ingesting CSV files into the data lake. The video concludes with a note to continue technical implementation in the next lecture.

What is the initial requirement for the data factory pipeline?

• To process JSON files

• To read data from Azure BLOB storage

• To generate reports

• To connect to a SQL database

What parameter is needed to indicate the file type being processed?

• File size

• File path

• File name

• File type

What does metadata provide information about?

• The size of the files

• The network speed

• The type of files

• The container and its files

Why is metadata about the last modified date important?

• To determine file size

• To filter files for processing

• To rename files

• To change file permissions

What is the final step in the pipeline process?

• Ingesting the file into the data lake

• Sending files via email

• Archiving the files

• Deleting the files