Balancing Segment Value Assignments Report

General Ledger◆ Seeded · Chart of accounts

Reports the assignment of primary balancing segment values to legal entities and ledgers across accounting setups, helping identify overlapping or unassigned values.

Sample build of the Balancing Segment Value Assignments 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

180

Segment values

Legal entities

Unassigned

Balancing Segment Value	Legal Entity	Ledger	Status
Sample	Acme Industrial	US Primary	Open
—	Northwind Trading	EU Primary	Posted
Sample	Globex Holdings	US Primary	Validated
—	Initech LLC	UK Primary	Open
Sample	Umbrella Corp	US Primary	Paid
Sample	Acme Industrial	US Primary	Open

AI Analyst · active

reading

The report reports which balancing segment values map to which legal entities and ledgers.

flag

Four balancing segment values aren't assigned to any legal entity — entries to them can't be attributed to an entity, breaking intercompany and statutory reporting.

root cause & next step

Assign every active balancing segment value to a legal entity; an unassigned value is a hole in the legal-entity structure.

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
FUN_ALL_BUSINESS_UNITS_V	dimension	dimension
GL_CODE_COMBINATIONS	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.

General Ledger 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
GL_LEDGERS	10	104
FUN_ALL_BUSINESS_UNITS_V	18	132
GL_CODE_COMBINATIONS	7	61

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 A setup-audit report; customers fold it into a governance dashboard that also surfaces orphaned segment values. Irvine rebuilds these on your data.