The Application Credit resource is used to issue credits to merchants that can be used towards future app purchases in Shopify. You can create an application credit by sending a request that includes the credit amount and a description explaining the reason for the credit. The total amount of all application credits requested by an app must not exceed the total amount the shop owner was charged in the last 30 days, or the total amount of pending payouts in the app’s Partner account.
The Application Credits pipeline can be used to request and retrieve details of the application credits from the shopify platform. Read more about this https://shopify.dev/docs/admin-api/rest/reference/billing/applicationcredithere,window=_blank]
Configuring the Credentials
Select the account credentials which has access to relevant Shopify data from the dropdown menu & Click Next
Select the dimensions you would like to fetch from the Shopify platform. You can click on View Schema anytime to see the schema of the table being created. Each of the selected dimensions will create one or more columns in the database table in the destination warehouse.
Specifies the manner in which data will get updated in the data warehouse : UPSERT will insert only new records or records with changes and APPEND will insert all fetched data at the end. Recommended to use "Upsert" option unless there is a specific requirement.
Default Value: UPSERT
Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.
- Manual Run
If scheduling is not required, you can use the toggle to run the pipeline manually.
- Normal Scheduling
Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.
- Advance Scheduling
Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.
Detailed explanation on scheduling of pipelines can be found here
Dataset & Name
- Dataset Name
Key in the Dataset Name(also serves as the table name in your data destination).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.
- Dataset Description
Enter a short description (optional) describing the dataset being fetched by this particular pipeline.
Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".
Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here
Still have Questions?
We’ll be happy to help you with any questions you might have! Send us an email at firstname.lastname@example.org.
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