Definition and discussion of Data Source and Data Sources.
In the context of ETL (Extract, Transform, Load) systems, a data source broadly refers to any location or system that provides data that can be extracted and transformed. This includes enterprise data stores from specific ERP, CRM, and other business systems.
For more about how to access specific sources see v2022.08 ETL+ Source Types
An ETL+ Data Source is a Source Type (ex.: MS SQL Server or NetSuite ODBC) with a Source Container (a specific data repository from a source type). Examples of data sources: an MS SQL Server database, an OData URL, or a NetSuite ODBC DSN.
Configuring an Existing Data Source
Reconfigure the settings of an existing data source in the ETL Source panel.
Open the v2022.08 ETL+ Extract, Transform and Load (ETL) Page page.
Enter the details to connect to your data source. See down below on this page for further information.
Changing an Existing Data Source Type
Use case: You open the Properties of a data source (see screenshot below) and it shows a MS SQL Server source. However, you want it to connect to an ODBC or Excel instead.
Then click the
Change Data Source icon (wrench icon) and select your new data source type.
Adding Data Sources
Use the ETL Source panel on the v2022.08 ETL+ Extract, Transform and Load (ETL) Page to add and manage data sources.
In single-tenant data warehouses, you can load the tables from each data source into one of the following data warehouse SQL schemas:
The default schema (typically the
Or into their dedicated data warehouse (dw) schema. Loading them into their own schema can facilitate user security, and segmentation of data warehouse tables by data source. Set up this option by selecting a data source, clicking the Properties icon, checking the “Dw Schema” checkbox (see example below), editing the source Alias if needed(which also defines the schema name), and clicking Save or Connect. Now this source’s tables will load into the dw schema = source’s Alias.