Azure Data Factory for Beginners - Build Data Ingestion - Add Dataset to Read Files

The lecture covers ensuring that filter activities produce CSV files, cloning and renaming datasets, adding parameters, and previewing and saving changes. It also discusses limitations of metadata CSV files datasets and concludes with next steps for ingesting files into the data leak.

What is the primary output format ensured by the filter activity?

• JSON files

• Text files

• XML files

• CSV files

What is the first step after cloning the bioload CSV metadata dataset?

• Adding a new column

• Renaming the dataset

• Deleting old data

• Exporting the dataset

What is the default filename set in the parameter setup?

• data.csv

• report.csv

• summary.csv

• finance.csv

Why is it necessary to create a dedicated dataset for reading files?

• To reduce processing time

• Due to limitations in reading metadata of the entire container

• To handle larger file sizes

• To improve data security

What issue arises when using nulls as a parameter value in the data factory?

• It cannot be processed

• It slows down the system

• It leads to incorrect data types

• It causes data corruption