This tutorial provides steps for creating a local file upload source connector to ingest local files to Platform using the user interface.
This tutorial requires a working understanding of the following components of Platform:
In the Platform UI, select Sources from the left navigation bar to access the Sources workspace. The Catalog screen displays a variety of sources for which you can create an account.
You can select the appropriate category from the catalog on the left-hand side of your screen. Alternatively, you can find the specific source you wish to work with using the search option.
Under the Local system category, select Local file upload, and then select Add data.
The Dataflow detail page allows you to select whether you want to ingest your CSV data into an existing dataset or a new dataset.
To ingest your CSV data into an existing dataset, select Existing dataset. You can either retrieve an existing dataset using the Advanced search option or by scrolling through the list of existing datasets in the dropdown menu.
With a dataset selected, provide a name for your dataflow and an optional description.
During this process, you can also enable Error diagnostics and Partial ingestion. Error diagnostics enables detailed error message generation for any erroneous records that occur in your dataflow, while Partial ingestion allows you to ingest data containing errors, up to a certain threshold that you manually define. See the partial batch ingestion overview for more information.
To ingest your CSV data into a new dataset, select New dataset and then provide an output dataset name and an optional description. Next, select a schema to map to using the Advanced search option or by scrolling through the list of existing schemas in the dropdown menu.
With a schema selected, provide a name for your dataflow and an optional description, and then apply the Error diagnostics and Partial ingestion settings you want for your dataflow. When finished, select Next.
The Select data step appears, providing you an interface to upload your local files and preview their structure and contents. Select Choose files to upload a CSV file from your local system. Alternatively, you can drag and drop the CSV file you want to upload into the Drag and drop files panel.
Only CSV files are currently supported by local file upload. The maximum file size for each file is 1 GB.
Once your file is uploaded, the preview interface updates to display the contents and structure of the file.
Depending on your file, you can select a column delimiter such as tabs, commas, pipes, or a custom column delimiter for your source data. Select the Delimiter dropdown arrow and then select the appropriate delimiter from the menu.
When finished, select Next.
The Mapping step appears, providing you with an interface to map the source fields from your source schema to their appropriate target XDM fields in the target schema.
Based on your needs, you can choose to map fields directly, or use data prep functions to transform source data to derive computed or calculated values. For comprehensive steps on using the mapping interface, see the Data Prep UI guide.
Once your mapping sets are ready, select Finish and allow for a few moments for the new dataflow to be created.
Once your CSV file is mapped and created, you can monitor the data that is being ingested through it using the monitoring dashboard. For more information, see the tutorial on monitoring sources dataflows in the UI.
By following this tutorial, you have successfully mapped a flat CSV file to an XDM schema and ingested it into Platform. This data can now be used by downstream Platform services such as Real-Time Customer Profile. See the overview for Real-Time Customer Profile for more information.