Azure Data Factory for Beginners - Build Data Ingestion - Requirements Discussion and Technical Architecture

The video tutorial explains how to source online sales data from Azure BLOB storage and ingest it into a data lake using Azure Data Factory. It covers setting up a linked service, creating JSON-based data sets, and implementing a copy data transformation activity to transfer data from the source to the sync data set in Azure Data Lake Gen. 2 storage. The tutorial concludes with a call to action for hands-on practice.

What is the primary task of the data engineering division in the context of the video?

• To design a new data lake

• To create an Azure Data Factory pipeline

• To develop a new web store

• To manage Azure BLOB storage

What format is the online sales file stored in within Azure BLOB storage?

• XML

• CSV

• JSON

• TXT

What is the purpose of a sync data set in the Azure Data Factory pipeline?

• To serve as a backup

• To monitor data flow

• To act as a data source

• To store the output data

Where is the sync data set stored according to the video?

• Azure Table Storage

• Azure Cosmos DB

• Azure Data Lake Gen. 2 storage

• Azure SQL Database

What activity is used to transfer data from the source to the sync data set?

• Data Movement Activity

• Copy Data Transformation Activity

• Data Flow Activity

• Data Sync Activity