How to consume CSV files in Azure Data Factory
In this post, we’ll walk you through the process of seamlessly consuming a CSV file and loading it into an Azure SQL database using Azure Data Factory. Here are the steps involved:
Step 1: Metadata Table Setup
To kick off the process, we create a metadata table that stores crucial information such as the file name and the SharePoint path, where we source our data. This table acts as a central repository for tracking our data sources.
Step 2: Foreach the results from the lookup
We initiate a For Each loop to iterate through the results obtained from the metadata lookup. This loop enables us to process each file systematically, ensuring comprehensive data ingestion.
Step 1: Metadata Table Setup
To kick off the process, we create a metadata table that stores crucial information such as the file name and the SharePoint path, where we source our data. This table acts as a central repository for tracking our data sources.
Step 2: Foreach the results from the lookup
We initiate a For Each loop to iterate through the results obtained from the metadata lookup. This loop enables us to process each file systematically, ensuring comprehensive data ingestion.
is table acts as a central repository for tracking our data sources.
Step 2: Foreach the results from the lookup
We initiate a For Each loop to iterate through the results obtained from the metadata lookup. This loop enables us to process each file systematically, ensuring comprehensive data ingestion.