Clear Ownership, Strong Controls, Trusted Data — With Evidence
Data Governance makes data discoverable, usable, secure, and compliant—so teams ship faster with fewer surprises and auditors get proof on demand.
SolveForce implements governance as a system across catalog, lineage, quality, privacy, contracts, access, and retention—wired to Zero Trust, DLP, and SIEM/SOAR—from streaming to warehouse to AI.
Connective tissue:
🧠 AI & RAG → /solveforce-ai • 📚 Standardization → /ai-knowledge-standardization
🏛️ Warehouse/Lake → /data-warehouse • 🔄 Pipelines → /etl-elt
🔐 Privacy & egress → /dlp • 🔑 Keys → /key-management • 🗝️ Secrets → /secrets-management • 🔒 Crypto → /encryption
👤 Identity → /iam • 🛡️ Security → /cybersecurity • 📊 Evidence/Automation → /siem-soar
☁️ Platform → /cloud • 🖧 Fabric → /networks-and-data-centers
🎯 Outcomes (Why SolveForce Governance)
- Trust at first use— clear owners, SLAs/SLOs, definitions, and lineage for every dataset.
- Less rework— data contracts and schema tests catch breakages before they ship.
- Safer by default— labels (PII/PHI/PAN/CUI), DLP, tokenization, and keys in HSM keep data lawful.
- AI-ready— curated, cited sources with access controls for guarded RAG and model pipelines.
- Evidence on demand— policy decisions, changes, and access logs exported to SIEM with WORM options.
🧭 Scope (What We Govern)
- Catalog & glossary— business definitions, owners, SLOs, classification, sensitivity, and tags.
- Lineage— column-level from source → pipeline → warehouse/lake → marts → AI features.
- Data contracts— schemas & SLAs for producers; schema registry (Avro/Protobuf/JSON) with compatibility rules.
- Quality— tests (nulls, ranges, uniqueness, PK/FK), metric parity, drift checks; break builds on critical failures.
- Access & privacy— ABAC/RBAC via IAM/SSO/MFA, labels (PII/PHI/PAN/CUI), tokenization, masking, and DLP.
- Retention & legal— records schedules, legal holds, deletion workflows, immutable archives.
- Residency & sovereignty— region-bound storage & compute, cross-border policies, routing guards.
- Streaming governance— topic taxonomy, retention/compaction, schema & PII controls, consumer ACLs.
- AI/ML governance— feature store lineage, model cards, data/label provenance, RAG “cite-or-refuse” enforcement.
- Reference/MDM— golden records, survivorship rules, match/merge, and change audit.
🧱 Building Blocks (Spelled Out)
- Catalog & Glossary-as-Code
- Terms & owners versioned in Git; PRs for changes; API-first updates; surfaced in BI and Notebooks.
- Lineage Everywhere
- Auto-capture from pipelines (dbt/Spark/Kafka/ELT), manual joins for edge tools; push to catalog and dashboards.
- Contracts & Registry
- –compatibility=BACKWARD (or stricter) on schemas; required data types/units/time zones; producer CI checks.
- Quality Gates
- Great Expectations/dbt tests at landing, transform, serve; quarantine lanes; policy-as-code denies promotion.
- Labels & Controls
- Classification tiers: Public / Internal / Confidential / Restricted + data classes (PII/PHI/PAN/CUI).
- Enforcement: dynamic masking, row/column security, tokenization, DLP egress rules. → /dlp
- Access & Identity
- SSO/MFA & groups map to catalog roles; short-lived credentials; approvals and least privilege by domain. → /iam
- Keys, Crypto, Secrets
- CMK/HSM custody (KMIP), envelope encryption, rotation/quorum; app secrets in vault, not in code.
→ /key-management • /encryption • /secrets-management - Observability & Evidence
- Freshness, lineage coverage, DQ pass rates, access decisions, PII scans; exports to SIEM/SOAR with WORM. → /siem-soar
🧰 Reference Patterns (Pick Your Fit)
A) Regulated Analytics (HIPAA/PCI/GDPR)
- Tokenize PAN/PII; PHI labeled & masked; region-bound stores; DLP egress blocks; immutable audit & backups.
B) Operational Data Products / Data Mesh
- Domain-owned tables with contracts; shared glossary; cross-domain SLAs; cost per data product tracked.
C) Streaming Governance (Kafka/Events)
- Topic naming standards, retention/compaction policies, schema registry enforced, PII redaction at edge, consumer ACLs & quotas.
D) AI & RAG Governance
- Curated sources → embeddings; label filters before ANN search; answers require citations or refusal; model cards + training data lineage.
→ /vector-databases • /solveforce-ai
E) Cross-Border & Residency
- Region sibling datasets; ETL replication rules; access broker enforces geo/tenant; legal-hold aware deletion.
📐 SLO Guardrails (Measure What Matters)
| SLO / KPI | Target (Recommended) |
|---|---|
| Freshness (curated tables) | ≤ 15–60 min (hot), per domain agreed |
| Data quality pass rate | ≥ 99% tests green per run |
| Lineage coverage (curated) | ≥ 95% column-level |
| PII/PHI labeling coverage | = 100% of new/changed datasets |
| Contract compatibility violations | = 0 in prod (blocked in CI) |
| Access decision latency (p95) | ≤ 100–300 ms |
| Subject-rights request SLA (privacy) | ≤ 30 days (or stricter by policy) |
| Evidence completeness (audits/IR) | = 100% (logs, approvals, artifacts) |
SLO breaches open tickets and trigger SOAR playbooks (rollback schema, quarantine dataset, revoke access, re-run jobs). → /siem-soar
🔒 Compliance Mapping (Examples)
- HIPAA / 42 CFR Part 2— labels + masking, minimum necessary, immutable logs/backups, access audit.
- PCI DSS— tokenization, key custody in HSM, WAF/Bot for APIs, DLP on egress, CDE segmentation.
- GDPR/CCPA— lawful basis, residency, DSR workflows (access/erasure), data minimization.
- SOX / ISO 27001 / SOC 2— change control, access, logging, incident & DR evidence.
- FedRAMP / CJIS / NIST 800-53/171— AC/IA/AU/SC/CM families aligned; continuous monitoring to SIEM.
📊 Operating Model (People, Process, Tech)
- Stewards & Owners— every table has a steward (SLAs/SLOs) and a product owner (roadmap, budget).
- Policy-as-Code— tagging, access, residency, retention, and schema rules validated in CI/CD.
- Backlog & Reviews— monthly DQ/lineage reviews; quarterly privacy & residency reviews; publish wins & RCAs.
- Unit Economics— $/TB scanned, $/1k queries, $/data product; visible in FinOps. → /finops
🛠️ Implementation Blueprint (No-Surprise Rollout)
1) Define domains & protect surface — data products, sensitivity, residency; business glossary & owners.
2) Stand up catalog & lineage — connect sources/pipelines; capture column-level; publish SLOs.
3) Contracts & registry — schemas in Git + registry; CI gates for compatibility & PII scans.
4) Quality & quarantine lanes — tests at landing/transform/serve; break builds on red; auto-quarantine.
5) Access & privacy — ABAC/RBAC; masking/tokenization; DLP egress; approvals audit.
6) Retention & legal — records schedules, legal hold, deletion workflows; immutable archives.
7) Observability & SIEM — freshness/DQ/lineage/labels/decisions on dashboards; export evidence to SIEM/SOAR.
8) AI guardrails — curated sources → vector DBs; cite-or-refuse; model cards & data lineage.
9) Operate & improve — monthly SLO & privacy reviews; quarterly contract & cost reviews; publish RCAs.
✅ Pre-Engagement Checklist
🔄 Where Data Governance Fits (Recursive View)
1) Grammar — data rides /connectivity & /networks-and-data-centers.
2) Syntax — curated truth lives in /data-warehouse via /etl-elt.
3) Semantics — /cybersecurity + /dlp preserve privacy & integrity.
4) Pragmatics — /solveforce-ai consumes governed truth with citations and guardrails.
5) Foundation — shared language via /ai-knowledge-standardization and the Codex.
6) Map — indexed across the /solveforce-codex & /knowledge-hub.
📞 Govern Data That People Trust—and Auditors Approve
Key terms in plain language
Open a term for a concise explanation of language used on this page.
Latency
The time it takes data to travel between two points. Lower latency improves voice, video meetings, cloud applications, gaming, and other real-time services.
Service-Level Agreement (SLA)
A provider’s written commitment covering service targets such as availability, response time, repair time, and sometimes financial credits when commitments are missed.
Cybersecurity
The practices and controls used to protect identities, devices, networks, applications, and data from unauthorized access, disruption, or manipulation.
Zero Trust
A security model that does not automatically trust a user or device because of its location. Access is continuously verified and limited to what is necessary.
Identity and Access Management (IAM)
The systems and policies that determine who a user is, what resources they may access, and how that access is authenticated and reviewed.
Multi-Factor Authentication (MFA)
A login control requiring more than one form of verification, such as a password plus an authenticator app, security key, or biometric factor.
API
An application programming interface is a defined way for software systems to exchange data or request functions from one another.
Artificial Intelligence (AI)
Software designed to perform tasks involving prediction, classification, generation, reasoning, or decision support. Business use still requires clear data, governance, security, and human accountability.