Azure Data Factory for Beginners - Build Data Ingestion - Reading from Source to Target - Part 1

The video tutorial covers the use of metadata-driven sources and syncs, starting with observing source-to-target details. It explains the process of ingesting files, setting up Azure BLOB storage, creating and uploading containers, and cloning pipelines. The tutorial also details configuring metadata-driven datasets, querying data, and testing for correct data retrieval. The lesson concludes with a summary and a preview of the next steps.

What is the first step in using metadata-driven sources and syncs?

• Observe source-to-target details

• Download necessary software

• Upload files to Azure

• Create a new data set

Which file is NOT mentioned as necessary for ingestion?

• Currency codes

• Customer data

• Products

• Online sales

What should you do after downloading the sales reference zip file?

• Rename the files

• Delete unnecessary files

• Extract it to a chosen folder

• Upload it directly to Azure

What is the purpose of creating a new container in Azure BLOB storage?

• To store backup files

• To delete old data

• To create a new database

• To organize uploaded files

What is the next step after uploading files to the Azure container?

• Clone the pipeline

• Run a data analysis

• Create a new data set

• Delete the container

Why is it important to supply parameters like system code and stage?

• To reduce processing time

• To filter records based on values

• To increase data size

• To enhance security

What is the final step before publishing the pipeline?

• Run a test

• Delete unused variables

• Create a backup

• Validate the setup