Azure Data Factory for Beginners - Build Data Ingestion - Add the For Each CSV File Activity and Test Ingestion

The video tutorial guides viewers through setting up a data ingestion pipeline using a for each activity to loop through files from a Bylot finance container. It covers configuring source and sync datasets, constructing directory strings using date functions, and validating and executing the pipeline. The tutorial concludes with checking the results in the data link storage account.

What is the initial task mentioned in the video regarding the dataset?

• To generate a report

• To analyze financial data

• To create a dataset for reading files

• To delete unnecessary files

What is the purpose of adding a 'for each' activity in the pipeline?

• To filter out unnecessary data

• To loop through each file and ingest it

• To delete duplicate files

• To create a backup of the data

How is the items array populated in the 'for each' activity?

• By importing from an external source

• By selecting the filter by file type activity

• By using a predefined list

• By manually entering file names

What is the role of dynamic content in configuring the copy activity?

• To manually input data

• To automate the data entry process

• To provide real-time data updates

• To supply source information and file names

What function is used to extract the directory name from the file name?

• Concatenate function

• Substring function

• Split function

• Merge function

Which function is used to get the current date and time?

• GetDate function

• UTC now function

• CurrentTime function

• TimeZone function

What is the final step before running the pipeline?

• Deleting temporary files

• Rewriting the script

• Validating the pipeline

• Debugging the code