In this hands-on lab scenario, you are a data engineer for Awesome Company. They would like to move some sales data from one Azure SQL database to another for archiving and analysis. You have been tasked with creating an Azure Data Factory pipeline to accomplish this task and to perform data transformations along the way. Performing the actions of this hands-on lab will help you become familiar with using Azure Data Factory to perform data migrations and transformations.
Successfully complete this lab by achieving the following learning objectives:
- Create a Destination Table for the Archived Data
Create a table in the acweb_arch database for the data to be sent to. Feel free to create one according to your own specifications, or copy and paste the code provided in the lab guide.
- Create a Pipeline to Move the Data
Create a pipeline that moves data from the production Azure SQL database (acweb) to the archive one (acweb_arch).
- Convert the Date Columns
The requesting team has specified that exact timestamps are not wanted in the archive environment because their analysis is only granular down to the day. Within your pipeline, perform a conversion for any columns of the datetime type so that only the day, month, and year are retained.