Azure Data Factory for Beginners - Build Data Ingestion - Write to Data Lake - Raw Plan

The video tutorial outlines the steps to handle a sync data set, starting with creating a finance container within a data engineering storage account. It explains the need for storage directories based on data type and introduces an event-driven data pipeline. The proposed storage structure is detailed, reflecting data delivery times. Finally, the creation of a sync data set with specific parameters is discussed.

What is the first step in handling the sync data set?

• Set up a data factory pipeline

• Develop a user interface

• Create a finance container

• Analyze the data structure

How are storage directories organized according to the tutorial?

• Alphabetically

• By data type

• By file size

• By user access level

What does 'event-driven' mean in the context of the data factory pipeline?

• The pipeline is dependent on user input

• The pipeline requires manual execution

• The pipeline is triggered by data upload events

• The pipeline runs on a fixed schedule

What is the proposed storage structure based on?

• Date and time of data delivery

• User access permissions

• File type and size

• Data source location

What parameters are included in the sync data set?

• User ID, access level, and timestamp

• Container, directory, and file name

• File size, type, and date

• Data source, destination, and format