Payables Matching Detail Report

Payables◆ Seeded · Invoices

Provides details of how an invoice, purchase order, or receipt was matched.

Sample build of the Payables Matching Detail Report — 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

12,400

Matched invoices

92%

3-way matched

$140K

Price/qty variance

Invoice	Po	Receipt	Matched Qty	Matched Amount	Variance
Sample	Sample	Sample	120	$1,240,500.00	Sample
—	—	—	45	$842,150.75	—
Sample	Sample	Sample	860	$96,400.00	Sample
—	—	—	12	$1,005,233.10	—
Sample	Sample	Sample	305	$58,720.40	Sample
Sample	Sample	Sample	120	$1,240,500.00	Sample

AI Analyst · active

reading

The report shows how each invoice matched to its purchase order and receipt.

flag

$140K of price and quantity variances fall within tolerance — small overages that pass automatically but add up.

root cause & next step

Review the variance pattern by supplier; tolerances that always absorb overages quietly erode margin.

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_INVOICE_LINES_ALL	dimension	dimension
RCV_TRANSACTIONS	dimension	dimension
Matched 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_DISTRIBUTIONS_ALL	59	11
AP_INVOICE_LINES_ALL	58	19
RCV_TRANSACTIONS	25	31

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 detail is line-by-line; AP wants a 3-way-match exception view summarizing where matches break. Irvine rebuilds these on your data.