Payables Payment Register

Payables◆ Seeded · Payments

Provides detailed information about payments made in Payables.

Sample build of the Payables Payment Register — reconciled, and rendered tool-neutral so it runs in Power BI, ThoughtSpot, or Tableau.

Sample build · illustrative

Filters

Period

FEB-26

Ledger

US Primary

Currency

USD

6,200

Payments

$78.00M

Paid

$640K

Voided/reissued

Payment	Supplier	Pay Date	Amount	Method	Status
Sample	Acme Industrial	2026-04-30	$1,240,500.00	Standard	Open
—	Northwind Trading	2026-03-31	$842,150.75	Corporate	Posted
Sample	Globex Holdings	2026-02-28	$96,400.00	Standard	Validated
—	Initech LLC	2026-01-31	$1,005,233.10	Default	Open
Sample	Umbrella Corp	2025-12-31	$58,720.40	Standard	Paid
Sample	Acme Industrial	2026-04-30	$1,240,500.00	Standard	Open

AI Analyst · active

reading

The report lists payments made in Payables with method and status.

flag

$640K of payments were voided and reissued — rework that usually points to bad bank details or returned payments.

root cause & next step

Trace voids to a cause such as a wrong remittance bank or expired account; a high void-and-reissue rate is avoidable friction.

Illustrative data. The live interactive version — drill-through, filters, export, and the AI Analyst — runs on your warehouse. See it live →

This is the report's BI Publisher data model — the SQL data set BI Publisher runs against Oracle tables to produce the output. The same SQL becomes a dbt model in your warehouse, so one definition drives both the formatted report and the analytics layer.

Data sources

How it interconnects: this data set reads the physical tables above. Those same tables surface in OTBI as subject areas and in BICC as PVOs — three lenses on one source. Open any table to trace its subject areas and View Objects.

The SQL data set is authored to this report's exact spec during the build and ships as the BI Publisher data model plus a matching dbt model — one definition, both layers.

The data-warehouse model — one fact surrounded by conformed dimensions (what you slice by) and measures (what you aggregate), expressed as dbt so it migrates with you. Grain: one row per source transaction.

●— fact → dimension join

Element	Type	Definition
AP_CHECKS_ALL	dimension	dimension
POZ_SUPPLIERS	dimension	dimension
Amount	measure	measure

Runs on your cloud warehouse — Snowflake, BigQuery, Redshift, or Synapse on AWS, Google Cloud, Azure, or any provider. Reconciled to the source control total — 0% variance by design. You own the code, the model, and the data.

How the data gets here: a BICC bulk extract of the source tables above, on the same pattern for every report. See the extraction pattern & data flow →

See the complete model

How this report's fact and dimensions fit the full picture, via conformed keys.

Payables data model →Enterprise model →

Every source object behind this report. Each linked table has its own page with full column descriptions, drawn from the Oracle BICC lineage and articulated for practitioners.

Table	Reporting columns	Subject areas
AP_INVOICE_PAYMENTS_ALL	22	2
AP_CHECKS_ALL	44	6
POZ_SUPPLIERS	145	75

Reporting columns = fields the report selects that are exposed as analytics attributes; subject areas = the OTBI subject areas the table appears in. Setup and configuration tables (master data, ledger and book setup, lookups) are referenced by the report's joins but aren't exposed as analytics columns or subject areas — that's expected, not a gap.

Customization note The seeded register is flat; teams rebuild it with payment-method, bank-account, and discount-taken analytics. Irvine rebuilds these on your data.