Revenue Technology Stack and Data Governance
What this domain tests
This domain tests the revenue stack architecture and the governance that keeps it trustworthy: system-of-record boundaries, integration patterns, field definitions, deduplication, compliance, and controls supporting revenue recognition.
Core rules
- Respect system-of-record boundaries. CRM owns accounts, contacts, and opportunities; marketing automation owns pre-opportunity engagement; CPQ, CLM, and billing own quote-to-cash; the CS platform owns post-sale health; the warehouse provides the unified analytical layer.
- Integration patterns differ: native connectors for simple syncs, iPaaS for orchestration and transformation, reverse ETL to push modeled data back into operational tools.
- Governance components: named data owners and stewards, documented field-level definitions, validation at point of entry, deduplication rules, a stable unique identifier, and a scheduled hygiene cadence.
- Compliance is architectural: consent capture under GDPR/CCPA, data residency, retention schedules, and access controls.
- Revenue recognition controls (ASC 606 / IFRS 15) require audit-grade system logs, approval trails, and evidence of delivery - not spreadsheet reconciliation.
- Stack rationalization weighs total cost of ownership and adoption, not feature lists.
Worked example
Two reps create the same prospect independently, producing duplicate accounts. Pipeline is double-counted and the forecast is overstated. Correct sequence: (1) define match rules, such as normalized domain plus fuzzy name; (2) merge with documented survivorship rules for field conflicts; (3) enforce validation at entry and block manual account creation when the domain already exists; (4) schedule a monthly dedupe audit; (5) reconcile pipeline reporting against the deduplicated account set. Order matters - deduplicate before reporting, and fix governance before automating anything downstream.
Traps
Buying tools before defining process. Letting each function maintain its own version of the truth. Treating governance as a one-time cleanup project. Running reverse ETL without a stable identifier. Assuming CRM data is audit-grade without controls.