WIP_ENTITIES
Schema: WIPmasterPer inventory orgThe WIP identity registry — every discrete job, repetitive assembly, and flow schedule claims its id and unique name here before type-specific detail lands in child tables; the anchor outside references point at
Shared across entity types — counting rows here is not counting jobs; filter ENTITY_TYPE. Purchasing's outside-processing distributions point at this table through their WIP_ENTITY_ID column.
What the badges mean
- master
- Data class: what the table holds — master data, transaction documents, control/configuration, interface/staging, or an APPS-schema view.
Fields
7 fields · 1 key
| # | Field | Description | Type | Flags |
|---|---|---|---|---|
| 1 | WIP_ENTITY_ID | The universal WIP key — globally unique; jobs, schedules, and outside references all carry it | NUMBER | Key |
| 2 | ORGANIZATION_ID | Inventory organization | NUMBER | |
| 3 | WIP_ENTITY_NAME | The job or schedule name users see — unique per organization | VARCHAR2 | |
| 4 | ENTITY_TYPE | Discrete job, repetitive assembly, or flow schedule — numeric, decode from your instance's manufacturing lookups | NUMBER | |
| 5 | DESCRIPTION | Entity description | VARCHAR2 | |
| 6 | PRIMARY_ITEM_ID | The assembly item being built | NUMBER | |
| 7 | GEN_OBJECT_ID | Genealogy object id for serialized tracking | NUMBER |
Field provenance: hand-curated. 1 key field.
Boilerplate SQL
Starting point for reading WIP_ENTITIESon Databricks — real DATE columns need no conversion, and the org anchor and the LAST_UPDATE_DATE watermark are already in place. Set your Unity Catalog location, schema, and org values below; they’re substituted into the SQL and the copy button.
-- ============================================================
-- Table : WIP_ENTITIES — The WIP identity registry — every discrete job, repetitive assembly, and flow schedule claims its id and unique name here before type-specific detail lands in child tables; the anchor outside references point at
-- Purpose: Column-selected read of WIP_ENTITIES — auto-generated from field metadata
-- Grain : One row per inventory org (ORGANIZATION_ID) + WIP_ENTITY_ID
-- Notes : Auto-generated skeleton for Oracle EBS R12 data landed in your lakehouse. Dates are real DATE/TIMESTAMP columns — no conversion needed. WHO audit columns omitted (see the quirks guide); the optional LAST_UPDATE_DATE watermark filter supports incremental extracts.
-- ============================================================
SELECT
t.WIP_ENTITY_ID AS "The universal WIP key — globally unique; jobs, schedules, and outside references all carry it",
t.ORGANIZATION_ID AS "Inventory organization",
t.WIP_ENTITY_NAME AS "The job or schedule name users see — unique per organization",
t.ENTITY_TYPE AS "Discrete job, repetitive assembly, or flow schedule — numeric, decode from your instance's manufacturing lookups",
t.DESCRIPTION AS "Entity description",
t.PRIMARY_ITEM_ID AS "The assembly item being built",
t.GEN_OBJECT_ID AS "Genealogy object id for serialized tracking"
FROM <catalog>.<schema>.WIP_ENTITIES t
WHERE
t.ORGANIZATION_ID = <inventory_org_id> -- inventory org, NOT the operating unit — see quirks guide #two-orgs
-- AND t.WIP_ENTITY_ID = <WIP_ENTITY_ID>
-- AND t.LAST_UPDATE_DATE >= TIMESTAMP '<watermark>' -- WHO watermark, bulk-stamped by batch jobs; see quirks guide #who-columns
ORDER BY t.WIP_ENTITY_ID;5 parameters not filled: <catalog>, <schema>, <inventory_org_id>, <WIP_ENTITY_ID>, <watermark>
Relationships
1-hop neighbors — click a table to navigate there. FND lookup decode and translation edges are highlighted; they’re the joins newcomers most often get wrong.
Join details
ON WIP_DISCRETE_JOBS.WIP_ENTITY_ID = WIP_ENTITIES.WIP_ENTITY_ID AND WIP_DISCRETE_JOBS.ORGANIZATION_ID = WIP_ENTITIES.ORGANIZATION_IDON WIP_ENTITIES.PRIMARY_ITEM_ID = MTL_SYSTEM_ITEMS_B.INVENTORY_ITEM_ID AND WIP_ENTITIES.ORGANIZATION_ID = MTL_SYSTEM_ITEMS_B.ORGANIZATION_IDON PO_DISTRIBUTIONS_ALL.WIP_ENTITY_ID = WIP_ENTITIES.WIP_ENTITY_ID