Charges

To charge a credit or a debit card, you create a Charge object. You can retrieve and refund individual charges as well as list all charges. Charges are identified by a unique, random ID.

The Charges pipeline can be used to request and retrieve details of the Charges from the Stripe platform. Read more about this here

Configuring the Credentials

Select the account credentials which has access to relevant Stripe data from the dropdown menu & Click Next

Credentials not listed in dropdown ?

Click on + Add New for adding new credentials

Data Pipelines Details

Data Pipeline

Select Charges from the dropdown

stripe charges list

Setting Parameters

Dimensions

Select the dimensions you would like to fetch from the Stripe 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.

Parameter Description Values

Delete or Append

Optional

This refers to the manner in which data will get updated in the data warehouse, with 'Delete' selected, the data will be upserted (only new records or records with changes) and with 'Append' selected, all data fetched will be inserted. Recommended to use "Delete" option unless there is a specific requirement.

{Delete, Append}

Default Value: Delete

Number of Days

Required

Enter the number of days for which you wish you get the data in each run.

'NUMBER'

stripe charges config

Datapipeline Scheduling

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 warehouse).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.

Notifications

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 info@datachannel.co.

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