Asset Reclassification Reconciliation Report

Fixed Assets◆ Seeded · Adjustments

Assets reclassified from one category to another in a period, with the cost and reserve moved between the old and new category accounts.

Sample build of the Asset Reclassification Reconciliation 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

Reclassifications

$2.10M

Cost moved

Reserve stranded

Asset	From Category	To Category	Cost Moved	Reserve Moved
Sample	Computer-Hardware	Computer-Hardware	$1,240,500.00	Sample
—	Buildings	Buildings	$842,150.75	—
Sample	Vehicles	Vehicles	$96,400.00	Sample
—	Furniture-Fixtures	Furniture-Fixtures	$1,005,233.10	—
Sample	Machinery	Machinery	$58,720.40	Sample
Sample	Computer-Hardware	Computer-Hardware	$1,240,500.00	Sample

AI Analyst · active

reading

The report shows the cost and reserve moved between the old and new category accounts.

flag

Cost and reserve net to zero across categories except one reclass where reserve didn't follow cost — the reserve was stranded on the old category.

root cause & next step

A reclass must move both cost and reserve; moving only cost leaves accumulated depreciation on the wrong account.

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
FA_BOOKS	dimension	dimension
FA_CATEGORIES_B	dimension	dimension
FA_TRANSACTION_HEADERS	dimension	dimension
Cost Moved	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.

Fixed Assets 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
FA_ADJUSTMENTS	8	3
FA_BOOKS	20	2
FA_CATEGORIES_B	5	10
FA_TRANSACTION_HEADERS	7	5

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 Reclass accounting is error-prone; the build proves cost and reserve net to zero across the moved categories. Irvine rebuilds these on your data.