In this hands-on lab scenario you are a data engineer for Awesome Company. You have been tasked with creating a batch processing solution in Azure that will analyze crowdsourced weather information. You have previously provisioned an Azure Data Lake Storage Gen2 account and containers for holding the uploaded files. Now you need to continue building upon that in order to analyze the data on a nightly basis. Performing the actions of this hands-on lab will help you become familiar with building a complete batch processing solution using Azure services.
Successfully complete this lab by achieving the following learning objectives:
- Prepare the Environment for Loading
- Upload files from GitHub to be processed.
- Configure the SQL Pool firewall to allow both your client IP address and other Azure services to connect.
- Create a table on the SQL Pool to hold the copied records for analysis.
- Copy the Weather Data Using Azure Data Factory
- Build a pipeline in Azure Data Factory to copy the weather data file records from the Azure Data Lake Storage Gen2 containers into Synapse Analytics.
- Along with data from the files, add extra columns for both the file path and the date processed.
- Delete the Weather Files
- Once the data has been copied, completely remove all files from the containers.