Search Results iscbv_bookings_base_fcv

Overview

ISCBV_BOOKINGS_BASE_FCV is a Supply Chain Intelligence (ISC) database view owned by the APPS schema in Oracle E-Business Suite 12.1.1 and 12.2.2. It functions as a supporting aggregation view for the Bookings fact base used by Oracle Supply Chain Intelligence and Demand Planning analytics. Its specific purpose, as documented in the ETRM repository, is to retrieve the latest pick release date associated with a sales order line. The "FCV" suffix conventionally denotes a "fact collection view" within the ISC/Demantra-derived analytics architecture, indicating that this object supplies derived measures to a fact table rather than serving as a transactional entry point. The view is documented as VALID, meaning it compiles against the referenced base objects without error in a standard, unmodified EBS installation.

The view does not store data. It is a read-only, non-updatable projection that aggregates inventory transaction request lines to produce a single pick-release date value per sales order line, which downstream bookkeeping and order-cycle-time analyses consume.

Underlying Base Objects

According to the documented view text, ISCBV_BOOKINGS_BASE_FCV is defined over a single base table: MTL_TXN_REQUEST_LINES. No other base objects are documented in the ETRM metadata, and the view definition contains no joins, unions, or subqueries. All filtering and aggregation is performed directly against MTL_TXN_REQUEST_LINES, the move order line table that records requests to move material within inventory, including pick-release activity generated during sales order fulfillment.

Because the view relies exclusively on MTL_TXN_REQUEST_LINES, its result set is bounded by the movement of stock in the warehouse. MTL_TXN_REQUEST_LINES is populated by Oracle Inventory's move order and picking processes, which are typically triggered automatically from shipping and order management workflows when a delivery is pick released.

Key Columns

• LINE_ID — Derived by aliasing TXN_SOURCE_LINE_ID from MTL_TXN_REQUEST_LINES. This column carries the sales order line identifier referenced by the move order line, making it the join key back to the Bookings fact base and the order line dimension.
• DATE_LATEST_PICK — Derived from MAX(PICK_SLIP_DATE). It represents the most recent pick release date recorded for the given sales order line. The MAX aggregation collapses multiple pick attempts or multiple pick slip dates on the same source line into a single value.

The view definition additionally restricts rows to transaction types 52 (Pick) and 53 (Pick—irreversible or confirmed pick variants) and to transaction source types 2 (Sales Order) and 8 (a related sales order-derived source). This filtering ensures that only pick-release events tied to sales order fulfillment are considered, excluding internal move orders, miscellaneous transfers, and other inventory activity.

Common Use Cases and Queries

The primary use case is populating or enriching a Bookings fact table with a "latest pick date" measure, enabling cycle-time analysis between order entry, pick release, and shipment. Analysts can then compute pick-to-ship lag, order-to-pick lag, and on-time pick performance by joining this value to shipment and order line data.

A representative query returns the latest pick date for a specific order line:

• SELECT line_id, date_latest_pick FROM apps.iscbv_bookings_base_fcv WHERE line_id = :order_line_id;

To join the measure to order lines and evaluate pick performance, the view is commonly queried as follows:

• SELECT ol.line_id, ol.ordered_item, f.date_latest_pick FROM apps.oe_order_lines_all ol, apps.iscbv_bookings_base_fcv f WHERE ol.line_id = f.line_id AND ol.header_id = :header_id ORDER BY ol.line_number;

Because LINE_ID may return multiple underlying move order lines collapsed into one row, no DISTINCT is required in the base view. When used in ISC fact processing, the view is typically joined to the bookings base view and aggregated further by date, organization, and order attributes before being loaded into the analytics fact table.