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Overview
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Overview

APPS.PA_REP_PROJ_SP_GL_V is a reporting view in the Oracle E-Business Suite Projects (PA) module. Its name reflects its purpose: a Project reporting view (PA_REP_PROJ) that combines project-level attributes with General Ledger period information (SP_GL), presumably supporting "sales pipeline" or "spread" style reporting against accounting periods. The view joins project master data, project classification, project player (team) information, probability values, and GL period definitions into a single denormalized structure suitable for direct query by reporting tools, Discoverer workbooks, and custom concurrent programs.

The view is owned by the APPS schema and is flagged in ETRM as Oracle Internal Use Only. Oracle Corporation does not support direct access to applications data through this object except from standard Oracle Applications programs. Consequently, developers should treat it as a read-only reporting object and expect its definition to change between releases without notice. It carries FND Design Data registration (PA.PA_REP_PROJ_SP_GL_V) and is marked VALID in the documented environments (12.1.1 and 12.2.2).

The user search term "expected_approval_date" maps directly to the column EXPECTED_APPROVAL_DATE (DATE), documented as "Project expected_approval_date" — the anticipated date on which a project is expected to receive approval, typically used in pipeline and forecast reporting.

Underlying Base Objects

The documented base objects underlying this view are:

The view therefore consolidates project, classification, team, status, probability, and GL calendar information without requiring the caller to replicate these joins.

Key Columns

  • PROJECT_ID, PROJECT_NUMBER, PROJECT_NAME — project identity and display attributes.
  • ORG_ID — operating unit / organization identifier, critical for Multi-Org security.
  • ORGANIZATION_ID — internal organization identifier used in project setup.
  • CLASS_CATEGORY, CLASS_CODE, CLASS_CODE_PERCENTAGE — classification category and code, with weighting.
  • PROJECT_ROLE_TYPE, PROJECT_PLAYER_PERSON_ID — the team member assigned to a role on the project.
  • PROBABILITY — percentage likelihood of winning the project, supporting pipeline weighting.
  • TYPE, STATUS — project type and current status description (resolved to up to 80 characters).
  • YEAR, QUARTER, GL_PERIOD, PERIOD_SET_NAME, GL_PERIOD_NUMBER — GL calendar context for period-based reporting.
  • EXPECTED_APPROVAL_DATE — the anticipated approval date for the project, central to pipeline and forecast reporting.
  • TOTAL_VALUE, NET_VALUE — gross and net project values used in revenue and pipeline analysis.
  • PRIMARY_CUSTOMER_NAME — the primary customer associated with the project.

Common Use Cases and Queries

Typical scenarios include pipeline forecasting by GL period, weighted revenue projections (NET_VALUE × PROBABILITY), customer-level rollups, and tracking of pending approvals by expected date. Because the view is unsupported for direct access, any custom code should be validated against the current release and wrapped defensively.

Example — projects with expected approvals in a GL period:

  • SELECT project_number, project_name, expected_approval_date, probability, total_value, net_value, primary_customer_name FROM apps.pa_rep_proj_sp_gl_v WHERE org_id = :p_org_id AND gl_period = :p_period AND expected_approval_date IS NOT NULL ORDER BY expected_approval_date;

Example — weighted pipeline by quarter for a customer:

  • SELECT year, quarter, gl_period, SUM(net_value * probability / 100) weighted_pipeline FROM apps.pa_rep_proj_sp_gl_v WHERE org_id = :p_org_id AND UPPER(primary_customer_name) LIKE UPPER(:p_customer||'%') GROUP BY year, quarter, gl_period ORDER BY year, quarter;

Example — projects approaching approval within a date range:

  • SELECT project_number, status, expected_approval_date, class_category, class_code FROM apps.pa_rep_proj_sp_gl_v WHERE expected_approval_date BETWEEN :p_from_date AND :p_to_date AND status NOT IN ('CLOSED','CANCELLED') ORDER BY expected_approval_date;

These patterns support pipeline reviews, approval backlog monitoring, and period-based financial projections while respecting Multi-Org filtering through ORG_ID.