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Data Governance Page

Version: 1.0
Date: September 7, 2025
Author: Product Team
Status: Draft

1. Feature Name​

Data Governance Page

2. Objective & Purpose​

To provide a central place for administrators and data stewards to manage data quality, view the health of all integrated data elements, and review an immutable audit trail of all critical plan changes. This page transforms high-level health scores into an actionable diagnostic tool and ensures SOX-level auditability.

3. Target Users​

  • ChainAlign Customer Success Manager: Uses the page to proactively identify and diagnose customer data issues.
  • Customer S&OP Lead / Data Steward: Uses the page to monitor data quality and assign corrective actions.
  • Customer Compliance Officer: Uses the page to review and export audit logs for regulatory compliance.

4. Functional Requirements​

The Data Governance Page will consist of two primary tabs: Data Health Dashboard and Plan Change Log.

4.1. Data Health Dashboard​

This tab provides a detailed, field-level inventory of a specific customer's integrated S&OP data.

  • 4.1.1. Header & Filtering:
    • The page will be headed by the customer's name and their overall Data Health Score.
    • It must include filtering options for the data catalog:
      • Filter by Health Status: Show only fields with "Critical," "Warning," or "Healthy" ratings.
      • Filter by Data Source: e.g., "Show all fields from SAP S/4HANA".
      • Filter by S&OP Data Flow: e.g., "Show all fields related to the Demand Flow".
  • 4.1.2. Customer Data Element Catalog & Quality Heatmap:
    • A detailed table providing a quality heatmap for each key data element.
    • Table Columns: Data Element, Source Field, Data Source, Data Owner, Quality Heatmap (Freshness / Completeness / Consistency), Overall Score.
  • 4.1.3. Heatmap Rating Logic:
    • The quality rating for each field is automatically generated by the Intelligent Data Ingestion & Validation Engine during each sync.
    • Freshness (SLA-based):
      • 🟢 Green: Source data timestamp is within the defined SLA (e.g., < 24 hours).
      • 🟡 Yellow: Timestamp is outside the SLA but within a secondary threshold (e.g., < 72 hours).
      • 🔴 Red: Timestamp is outside the secondary threshold.
    • Completeness (Null Percentage):
      • 🟢 Green: < 2% null values.
      • 🟡 Yellow: 2-10% null values.
      • 🔴 Red: > 10% null values.
    • Consistency (Validation Rules):
      • 🟢 Green: 100% of values pass validation rules (e.g., data type, range).
      • 🟡 Yellow: Some values failed validation but were successfully auto-corrected by the system.
      • 🔴 Red: Some values failed validation and could not be auto-corrected.

4.2. Plan Change Log​

This tab provides an immutable, auditable log of all critical changes to planning data.

  • 4.2.1. Log Content:
    • The log must be presented in a table view.
    • Each entry must contain: Timestamp, User, User Role, Data Element Changed, Old Value, New Value, and Business Justification (if captured during a "Consensus Lock-In" or "Executive Override").
  • 4.2.2. Immutability:
    • The log must be append-only. No user, including an admin, can edit or delete a log entry.
  • 4.2.3. Filtering & Export:
    • Users must be able to filter the log by a date range, user, and data element.
    • Users must be able to export the filtered view to a CSV file for audit purposes.

5. User Journeys​

  • User Journey 1 (Customer Success Manager):

    1. The CSM reviews the main Customer Health Monitoring Dashboard and sees a customer's Data Health Score has dropped.
    2. They drill down to the Data Governance Page for that customer.
    3. Using the filters, they isolate the fields with "Critical" quality.
    4. They identify that On_Hand_Units has a red Freshness score. Hovering over it reveals the source transaction is 4 days old.
    5. They contact the customer's designated Data Owner with a specific, actionable diagnosis to resolve the issue.

  • User Journey 2 (Compliance Officer):

    1. An external auditor requests a log of all changes made to the Q3 revenue forecast.
    2. The Compliance Officer navigates to the Plan Change Log tab.
    3. They filter by the Q3 date range and the Revenue_Forecast data element.
    4. They export the resulting view to a CSV file and provide it to the auditor, satisfying the request in minutes.

6. Dependencies​

  • Intelligent Data Ingestion & Validation Engine: This engine is responsible for generating and updating the quality scores that power the Data Health Dashboard.
  • Consensus Lock-In Protocol & Executive Override Feature: These features are responsible for generating the events that are recorded in the Plan Change Log.
  • User Authentication & Roles System: Required to log the correct user and role for all changes.