Product Smart Collection
A smart collection is a grouping of products defined by rules that are set by the merchant. Shopify automatically changes the contents of a smart collection based on the rules. Smart collections, like other types of collections, are used to break down the catalog of products into categories and make the shop easier to browse. By default, a store can have up to 5000 smart collections.
The Product Smart Collection pipeline can be used to request and retrieve details of the product smart collection from the shopify platform. Read more about this here
Configuring the Credentials
Select the account credentials which has access to relevant Shopify data from the dropdown menu & Click Next
- Dimensions
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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.
Setting Parameters
Parameter | Description | Values |
---|---|---|
Insert Mode |
Optional 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. |
{Upsert, Append} Default Value: UPSERT |
Fetch Mode |
Optional Specifies the manner in which data will fetched from the Shopify API : FULL will fetch the entire object and INCREMENTAL will only fetch the new records after the latest update. |
{Full, Incremental} Default Value: FULL |
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
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If scheduling is not required, you can use the toggle to run the pipeline manually.
- Normal Scheduling
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Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.
- Advance Scheduling
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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
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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
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Enter a short description (optional) describing the dataset being fetched by this particular pipeline.
- Notifications
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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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