Payables Posted Payment Register

Payables◆ Seeded · Period close

Lists accounting lines for payments transferred to the general ledger.

Run note · Performance The subledger (XLA) join — especially Projects-to-XLA — is a known BI Publisher performance trap on large ledgers. Pre-join it in the warehouse, or apply tight ledger, period, and source filters before running online.

Sample build of the Payables Posted 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

6,100

Payments posted

$77.00M

Transferred to GL

$0 diff

Ties to GL

Payment	Supplier	Account	Entered Debit	Entered Credit	Accounting Date
Sample	Acme Industrial	1000-2100-000	$1,240,500.00	$1,240,500.00	2026-04-30
—	Northwind Trading	1000-5400-000	$842,150.75	$842,150.75	2026-03-31
Sample	Globex Holdings	1000-1410-000	$96,400.00	$96,400.00	2026-02-28
—	Initech LLC	2000-2100-000	$1,005,233.10	$1,005,233.10	2026-01-31
Sample	Umbrella Corp	1000-6300-000	$58,720.40	$58,720.40	2025-12-31
Sample	Acme Industrial	1000-2100-000	$1,240,500.00	$1,240,500.00	2026-04-30

AI Analyst · active

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The report lists the accounting lines for payments transferred to the general ledger.

flag

Payment accounting ties to GL except where a payment's cash-clearing entry hasn't posted — the cash side lags the liability relief.

root cause & next step

Confirm cash-clearing accounting posted for every payment; an unposted clearing entry leaves cash and AP out of step.

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
XLA_AE_LINES	dimension	dimension
XLA_AE_HEADERS	dimension	dimension
Entered Debit	measure	measure
Entered Credit	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
XLA_AE_LINES	23	17
XLA_AE_HEADERS	16	19

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 Same — best consumed as part of a reconciled AP subledger-to-GL view. Irvine rebuilds these on your data.