Domain catalogue Finance on Snowflake

Bank and payment details on Snowflake

Bank accounts of customers, suppliers and the company's own entities, verified before use, masked by default and audited on every read.

SOURCES, READ IN PLACESnowflakelakehouseASSEMBLED1 · standardise2 · match on the domain keys3 · survive field by field4 · place in the hierarchies5 · run the column and row rules6 · publish the golden viewGOLDEN BANK AND PAYMENT DETAILSBank and payment detailsone id · every source key keptREAD BYGrids, pivots and drill-downswith the transactionsAPIs, SQL and agentsone policyWrite-back to the systemsacknowledged
The objects the domain reads in place on Snowflake, the assembly steps, and who reads the result. Writes go through MERGE into a governed schema.
2
objects read in place from Snowflake
catalogue
4
attribute groups assembled
catalogue
3 days
to production-grade
estimate
1
write path, acknowledged and logged
catalogue
0
rows copied to start
product
What the domain reads

The Snowflake objects behind the golden record

Tables are read in place through the Snowflake connector with filters and aggregates pushed down; nothing is copied out.

ObjectRead fromFields the domain usesFreshness
Bank accountCONFORMED.BANK_ACCOUNTaccount_key · party_key · iban_hash · last4 · bic · status · verified_onas fresh as the landing pipeline; live for governed tables
PaymentCONFORMED.PAYMENTpayment_id · account_key · amount · dateas fresh as the landing pipeline; live for governed tables
The keys

How bank and payment details records match, in this system's fields

IBANaccount number + bank key + countryholder name and party (fuzzy)

The first object above carries the strong keys; the standardised attributes come from the same rows. A bank account is master data with a verification record; a change creates a pending version that stays unusable until verified.

What is written back

Through the interfaces Snowflake supports

Golden records and their history are written with MERGE into a governed schema, so the warehouse always carries the current keys.

InterfaceUsed forResult
MERGE INTO GOLDEN.BANK_ACCOUNT on the golden key; history in GOLDEN.BANK_ACCOUNT_HISTORYgolden values approved for write-back: account; verification; usagethe id or error Snowflake returns, stored beside the change

Write-back is off per object until a test write succeeds, and approval rules can require a person per object. Reconciliation compares the source row with the golden value on a schedule.

Access and prerequisites

What is in place before the first build

Snowflake roles and row access policies are honoured; Lima adds its own layers on top.

Register the objects2 objects from the connector catalogue; each shows its rows at once.
Nearby

This domain on other systems, and other domains on Snowflake

Bank and payment details on

Other domains on Snowflake

Terms on this page

VerificationThe recorded check that a bank account belongs to the party, with method and evidence.
MaskingShowing only part of a value, with the full value available to authorised roles and logged.
Read in placeThe rows stay in Snowflake; Lima sends the filter and the columns and Snowflake returns the matching rows.
Questions

Does this domain copy data out of Snowflake?

The golden record reads the objects above in place. History the pivot needs at scale is landed in your lake by the Backbone, under the same keys, security and audit.

What does the Snowflake team need to do?

Grant the read access and the write interfaces listed above and agree the refresh method. Nothing is installed in Snowflake.

Can we start with reads only?

Yes. Write-back stays off per object until a test write succeeds; the golden view, the API and the pivots work from day one on reads.

See your first domain built on your data

Bring two systems that hold the same customers, suppliers or materials. In one working day we connect them, run the match on live rows, review the queue with your steward and publish the first golden view with its API.