Data Stack Audit Checklist

A comprehensive audit checklist used by Valiotti Data in 50+ company assessments. Use this to evaluate your current data stack maturity and identify gaps before they become costly problems.

Infrastructure

• Cloud data warehouse deployed (Snowflake, BigQuery, Redshift, or Databricks)
• ETL/ELT pipeline tool in place (Fivetran, Airbyte, dbt, or custom)
• Data ingestion covers all critical sources (CRM, billing, product, marketing)
• Staging, transform, and mart layers separated in the warehouse
• Source-of-truth tables documented and version-controlled
• Disaster recovery plan for data infrastructure tested in last 12 months

Governance

• Data dictionary or catalog exists and is actively maintained
• PII/sensitive data classified and access-controlled
• Data retention and deletion policies documented
• GDPR/CCPA compliance verified for all data flows
• Data quality monitoring with automated alerts (freshness, volume, schema)
• Ownership assigned for every critical dataset

Analytics

• Self-serve BI tool deployed (Looker, Metabase, Tableau, Power BI)
• Executive dashboard with 5-7 north star metrics
• Departmental dashboards for Sales, Marketing, Product, Finance
• AB testing framework with statistical significance checks
• Attribution model implemented and validated
• Metric definitions consistent across all reports

Team & Process

• Dedicated data owner or fractional CDO role filled
• Analytics requests tracked with SLA (not ad-hoc Slack asks)
• Data team has documented onboarding process
• Stakeholder data literacy training conducted
• Regular data quality review cadence (weekly or bi-weekly)
• Cost monitoring for cloud data spend

Scoring

Count your checks:

• 20-24: Mature data stack. Focus on optimization and advanced use cases.
• 14-19: Solid foundation with gaps. Prioritize governance and self-serve analytics.
• 8-13: Early stage. You need a data strategy roadmap — let’s talk.
• 0-7: Critical gaps. A Fractional CDO engagement could save 6+ months of misdirection.