Guide

Standing up a DG Foundation program in 30 days

A phased playbook for reaching an audit-ready governance baseline, starting with your highest-priority domains.

By the Procela team · 7 min read

Most data governance initiatives stall not because the tools are missing, but because the program never becomes operational. Policies live in documents, ownership is ambiguous, and the connection between discovery, access control, and audit is manual. The DG Foundation track is designed to get past that — to a running baseline you can defend in an audit — in about thirty days.

What a “baseline” actually means

A governance baseline isn't a finished program; it's the smallest version that stands on its own. Concretely, at the end of the first phase you should have:

The scope is deliberately narrow. You are not trying to govern everything — you are proving the loop closes for the data that matters most.

Week 1 — Connect and scope

Deploy Procela's edge connector inside your environment and connect your databases, warehouses, and dbt — sources like PostgreSQL, SQL Server, Oracle, Snowflake, BigQuery, Redshift, and Databricks. Only metadata leaves your perimeter. In parallel, pick the domains for Phase 1 — usually the ones under the most regulatory pressure, such as CUI, PII, or export-controlled engineering data.

Week 2 — Classify and reconcile

Register your in-scope assets and let Procela's AI suggest classifications, then reconcile them against your chosen domains. The AI-assisted suggestions are review-gated, so a steward confirms anything unlabeled before it takes effect. The goal here is coverage: every asset in scope has a known classification and a home domain.

Week 3 — Assign stewardship

Map owners, stewards, and agents to domains and assets. Procela derives a RACI matrix from those role and process-ownership assignments, so accountability is explicit rather than implied. This is the step most programs skip — and the reason audits turn into fire drills later.

Week 4 — Govern and audit

Author your first policies in plain language and record the controls that implement them — access, retention, export controls — against the assets they govern. Every change lands in a tamper-evident audit trail, so audit prep becomes a query rather than a project.

Common pitfalls

After Phase 1

Once the baseline is live, expanding is mostly a matter of adding domains — the catalog, stewardship model, and audit trail are already in place. The hard part, going from zero to a running program, is behind you.

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