Azure Data Factory for Beginners - Build Data Ingestion - Add Orchestration Pipeline - Part 1

The video tutorial guides viewers through creating an orchestration pipeline in Azure Data Factory. It covers setting up folders, creating pipelines, defining variables, inserting batch details, clearing logs, and configuring lookup activities. The tutorial concludes with saving, validating, and publishing the pipeline, preparing for further development in the next lesson.

What is the first step in creating an orchestration pipeline?

• Creating a new database

• Deleting old logs

• Setting up a new folder

• Running a batch script

Which variable is set to indicate the frequency of the batch run?

• V_frequency

• V_system

• V_daily

• V_code

What is the purpose of clearing the pipeline log?

• To archive old data

• To ensure a clean slate for new runs

• To increase storage space

• To update the system code

What activity is used to retrieve batch run details in Azure Data Factory?

• Lookup activity

• Copy activity

• Delete activity

• Insert activity

What should be unchecked to return more than one row in the lookup activity?

• First row only

• All rows

• Batch details

• Stored procedure

What happens to the run status when batch details are retrieved?

• It remains not started

• It changes to completed

• It is deleted

• It changes to in progress

What is the final step before publishing the pipeline?

• Clear logs

• Insert batch details

• Run a preview

• Validate all