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Found 6 Skills
Set org-wide revenue data governance policy - which system is source of truth per object class (account, contact, opportunity, subscription, usage event, revenue metrics), how cross-team data contracts bind producers to consumers, where revenue metric definitions live, and who arbitrates disputes. Produces a per-object SOR/SOT designation table, an identity-resolution spine, a data-contract register, and a federated ownership model. Use whenever the user mentions source of truth, "two ARR numbers", GTM data contracts, revenue data governance, metric definition ownership, or "finance and sales report different numbers" - even if they never say "governance". Covers B2B, PLG/B2C, hybrid. Do NOT use for CRM field-level rules - use mbfinotti/revops-skills@crm-data-governance instead.
Build reliable data pipelines and analytics-ready datasets. USE when cleaning data, designing ETL/ELT, defining contracts, or shipping reproducible data workflows.
Use this skill when implementing data validation, data quality monitoring, data lineage tracking, data contracts, or Great Expectations test suites. Triggers on schema validation, data profiling, freshness checks, row-count anomalies, column drift, expectation suites, contract testing between producers and consumers, lineage graphs, data observability, and any task requiring data integrity enforcement across pipelines.
Use when defining events, fields, and governance for GTM analytics pipelines.
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
Analyzes and designs batch and streaming data pipelines with contracts, lineage, reliability, and cost controls. Use for ingestion and transformation systems. NOT for ad-hoc analysis or schema design.