revops-data-governance

What problem does it solve?

Revenue teams lose trust in reporting when CRM data has unclear ownership, inconsistent definitions, conflicting values across systems, and uncontrolled field growth.

Core Features & Use Cases

• Data model governance across the bow-tie: Ensures objects, properties, and relationships map to the customer lifecycle so reporting can connect contacts, accounts, opportunities, and revenue.
• Field/property governance: Enforces naming conventions, approval workflows, data dictionary discipline, and safe deprecation so the CRM stays usable as it scales.
• Data quality operations and dedup strategy: Defines quality dimensions and scoring, installs validation and detection systems, and standardizes merge protocols to reduce duplicates and drift.
• Integration and enrichment rules: Establishes system-of-record ownership, sync direction, conflict resolution, monitoring, and GDPR-aware enrichment practices.
• Definition governance and semantic layer foundations: Aligns measurable definitions (pipeline, lead, customer, stages) so dashboards and AI-driven decisions share a single meaning.

Quick Start

Use the revops-data-governance skill to run a data quality audit and then specify the prevention rules needed to stop CRM field and definition sprawl before doing any cleanup.