The Issuing objects represented within Sigma or Data Pipeline includes Authorizations, Transactions, Cards, and Cardholders. Issuing-specific tables can be found within the Issuing section of the schema.
Issuing data for your connected accounts can be found within tables prefaced with
connected_account_, for example,
connected_account_issuing_authorizations. More information about using Connect with Sigma or Data Pipeline can be found in the Connect section of the documentation.
Whenever an issued card is used to make a purchase, an Authorization object is created. Each row within the
issuing_authorizations table represents data about this object. The same information can be retrieved through the API and is available in the Stripe Dashboard. Note that the request history field isn’t currently available. Every authorization that has been created on your account is available in Sigma or Data Pipeline.
card_id column of this table stores the ID of the card used to make the purchase. You can find additional information about the card that initiated the authorization by joining the column with the
To access the transactions associated with a particular authorization, you can join the
authorization_id column in the
The following query computes counts of authorizations grouped by approval status.
select date_trunc('month', created) as month, count(case when approved then 1 end) as num_approved_authorizations, count(*) as total_num_authorizations from issuing_authorizations where date_trunc('month', created) between date_trunc('month', date_add('month', -13, date(data_load_time))) and date_trunc('month', date_add('month', -1, date(data_load_time))) group by 1 order by 1 desc, 2 limit 2
An Issuing Transaction object represents any use of an issued card that results in funds entering or leaving your Stripe account, such as a completed purchase or refund. The
issuing_transactions table stores information about these objects. You can retrieve the same information through the API, and it’s also available in the Stripe Dashboard.
For additional details about the transaction, such as the fee, you can access the associated balance transaction. You can do this by joining the
balance_transaction_id column with the
id column of the
balance_transactions table. Balance transactions are not Issuing-specific objects. More information about working with balance transactions in Sigma or Data Pipeline can be found in the Transactions section of the documentation.
authorization_id column allows you to access the Authorization object associated with the Transaction by joining on the
id column of the
issuing_authorizations table. This can provide additional details about how the transaction was authorized. The
authorization_id column on an Issuing transaction can be empty in the event of force capture and for some instances of refunds.
You can also access both the card and cardholder involved in the transaction via the
cardholder_id columns. Information about the card is stored in the
issuing_cards table, and information about the cardholder is stored in the
issuing_cardholders table. The Card and Cardholder objects can provide additional details about who initiated the transaction.
The following query returns information about the three most recent over captures. It joins the
issuing_authorizations table to determine if this transaction is an over capture by comparing the amounts of the two objects.
select date_format(it.created, '%Y-%m-%d') as day, it.id, ia.amount as authorized_amount, -1 * it.amount as captured_amount from issuing_transactions it join issuing_authorizations ia on it.authorization_id=ia.id where it.type='capture' and -1 * it.amount > ia.amount --- This checks if this transaction was overcaptured order by day desc limit 3
One of the benefits of using Sigma or Data Pipeline with Issuing is the ability to aggregate data. The following example joins the
balance_transactions table and aggregates each of the types of fees for Issuing transactions by month.
select date_trunc('month', it.created) as month, fd.type as fee_type, sum(fd.amount) as net_fees, sum(it.amount) as net_amount from issuing_transactions it inner join balance_transactions bt on bt.id=it.balance_transaction_id inner join balance_transaction_fee_details fd on fd.balance_transaction_id=bt.id group by 1,2 order by month desc, fee_type
issuing_cards table contains data about an individual Card object. The same information is available through the API and within the Stripe Dashboard. The spending controls field isn’t currently available.
Every issued card has an associated Cardholder, which can be accessed by joining the
issuing_cardholders table on the
Cardholder data is stored within the
issuing_cardholders table. The same information can be retrieved through the API or with the Stripe Dashboard. The spending controls field isn’t currently available.
This table can be joined to other tables to provide information about the entity that initiated a transaction or owns an issued card.
The following example retrieves information about the three most recently created active cardholders.
select date_format(created, '%Y-%m-%d') as day, id, email, type from issuing_cardholders where status='active' limit 3
Metadata for each Issuing object is stored in a separate table. The names of these tables is the name of the object’s table with the addition of
_metadata to the end, for example,
issuing_transactions_metadata. The metadata table contains a foreign key to the corresponding object in the primary table that you can use to join the two tables. For example, every row in the
issuing_transactions_metadata table has the column
issuing_transaction_id that references the
id column of a row in the
The following example creates a dictionary from the
issuing_transactions table’s metadata table. It then uses it to access the value of the metadata key
'my_label' for several transactions.
with transactions_metadata_dictionary as ( select issuing_transaction_id, map_agg(key, value) metadata_dictionary from issuing_transactions_metadata group by 1 ) select date_format(it.created, '%Y-%m-%d') as day, it.id, it.amount, metadata_dictionary['my_label'] as my_label_value from issuing_transactions it left join transactions_metadata_dictionary on it.id = transactions_metadata_dictionary.issuing_transaction_id where element_at(metadata_dictionary, 'my_label') is not null order by day desc limit 3