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Data Management & Data Governance Process Templates
Editable data management process templates for governance, quality, master data, catalogs, access, lifecycle, engineering, migration and AI oversight.
Start with an editable operating process for the work enterprise data teams perform every day: assigning ownership, resolving quality issues, certifying catalog records, approving access, documenting lineage, governing AI use cases, building pipelines and moving data safely between systems. Each template makes the decision rights, technical handoffs, evidence and exception routes visible across business, stewardship, governance, risk and technology roles.
Data governance is the set of processes that decide who owns a dataset, what it means, how good it has to be, where it came from and when it may be deleted, in that order: an operating model gives stewards their mandate, the governance decision process scopes an issue, assigns an owner and records the decision, and the catalog, quality, lineage and lifecycle processes then run against that authority. There is no standalone data policy or records retention schedule template; both appear as stages inside the operating model and the lifecycle chart.
Data quality and master data are the two disciplines that decide whether a number can be trusted and whether two records are the same customer: a rules-and-monitoring process, a defect process for one issue, a master data process for shared entities, and the glossary and catalog that give every rule and record a defined meaning. Data engineering and migration covers moving data reliably, either every day through a pipeline or once, when a system is replaced, from scope assessment to cutover, with the lineage documentation both produce.
Two governance families are cross-listed because data programs run them. AI governance screens a use case before delivery starts and keeps every AI system's purpose, risk tier and controls connected from inventory to retirement. Access governance grants, reviews and revokes a data access request on the same loop as any other entitlement; periodic access recertification exists only as the tail step of those charts, not as a template of its own.
Turn data policy into executable work
Data programs fail when ownership exists only in a policy, quality issues disappear into tickets, catalog records have no accountable reviewer, or migration and pipeline decisions are separated from business validation. These vendor-neutral templates connect governance decisions to implementation and verification without claiming one operating model fits every organization. Adapt domains, authority limits, classifications, risk criteria, review cadence and evidence to your policies and applicable requirements.
Featured templates
- Data governance process flowchart (issue to closure)
Data governance process template for scoping issues, assigning ownership, assessing cross-domain impact, recording decisions, implementing actions and closing with evidence.
- Data quality management process flowchart
Data quality management process template for prioritizing critical data, defining measurable rules, monitoring results and sustaining preventive improvements over time.
- Data catalog process flowchart (register to certify)
Data catalog process template for registering an asset, enriching metadata, assigning stewardship, validating user context, certifying status and maintaining the record.
- Data migration process flowchart (assessment to cutover)
Data migration process template for scope assessment, field mapping, cleansing, mock loads, reconciliation, business validation, cutover checks and controlled rollback.
Process families
Data governance
Data governance is the set of processes that decide who owns a dataset, what it means, how good it has to be, where it came from and when it may be deleted. The six templates in this family follow that order: an operating model gives stewards their mandate, a decision process settles disputes, and the catalog, quality, lineage and lifecycle processes then run against that authority.
- Data governance operating model template
Data governance operating model template for defining the mandate, domains, decision rights, stewardship roles, forums, rollout plan, measures and periodic review.
- Data governance process flowchart (issue to closure)
Data governance process template for scoping issues, assigning ownership, assessing cross-domain impact, recording decisions, implementing actions and closing with evidence.
- Data catalog process flowchart (register to certify)
Data catalog process template for registering an asset, enriching metadata, assigning stewardship, validating user context, certifying status and maintaining the record.
- Data quality management process flowchart
Data quality management process template for prioritizing critical data, defining measurable rules, monitoring results and sustaining preventive improvements over time.
- Data lineage documentation process flowchart
Data lineage documentation process template for scoping an output, tracing source dependencies, mapping transformations, validating evidence and maintaining changes.
- Data lifecycle management process flowchart
Data lifecycle management template covering acquisition, validation, classification, storage, use, sharing approval, retention, legal holds, archiving and evidenced disposal.
Also part of this family
- Business glossary process flowchart (proposal to published term) — Business glossary process template for proposing terms, drafting definitions, resolving duplicates, steward and owner approval, catalog publication, review, revision and retirement.
- Data access request process flowchart (request to revocation) — Data access request process flowchart: state the purpose, read the dataset's classification, let the data owner decide, run the personal-data checks, grant time-boxed access, then recertify or revoke.
Data quality and master data
Data quality and master data are the two disciplines that decide whether a number can be trusted and whether two records are the same customer. This family groups the five templates that run them: a rules-and-monitoring process, a defect process for one issue, a master data process for shared entities, and the glossary and catalog that give every rule and record a defined meaning.
- Data quality management process flowchart — Data quality management process template for prioritizing critical data, defining measurable rules, monitoring results and sustaining preventive improvements over time.
- Data quality issue management process flowchart — Data quality issue management template for reporting one defect, assessing impact, containing use, confirming cause, remediating data and closing with evidence.
- Master data management process flowchart — Master data management process template for validating requests, matching records, approving changes, publishing identifiers, maintaining attributes and retiring records.
- Business glossary process flowchart (proposal to published term) — Business glossary process template for proposing terms, drafting definitions, resolving duplicates, steward and owner approval, catalog publication, review, revision and retirement.
- Data catalog process flowchart (register to certify) — Data catalog process template for registering an asset, enriching metadata, assigning stewardship, validating user context, certifying status and maintaining the record.
Data engineering and migration
Data engineering and migration cover the work of moving data reliably, either continuously through a pipeline that runs every day or once, when a system is replaced. The four templates here are the pipeline development process, the migration process from scope assessment to cutover, the lineage documentation both produce, and the enterprise implementation whose migration stage they expand.
- Data pipeline development process flowchart — Data pipeline development template for contract design, versioned build, replay testing, security review, data-quality gates, deployment, monitoring and failure handoff.
- Data migration process flowchart (assessment to cutover) — Data migration process template for scope assessment, field mapping, cleansing, mock loads, reconciliation, business validation, cutover checks and controlled rollback.
- Data lineage documentation process flowchart — Data lineage documentation process template for scoping an output, tracing source dependencies, mapping transformations, validating evidence and maintaining changes.
- Enterprise Software Implementation Process — Enterprise software implementation template covering discovery, requirements, design, configuration, integration, data migration, testing, UAT, go-live, hypercare and handover.
AI governance
- AI governance process flowchart (inventory to retirement) — Policy-neutral AI governance process template for inventory, risk tiering, control selection, independent review, deployment decisions, monitoring, reassessment and retirement.
- AI use case approval process flowchart — AI use case approval template for single-use-case intake, value, data, feasibility and risk review, conditional approval, recorded decisions and delivery handoff.
Access governance
Access governance is the lifecycle of a person's entitlements. An HR event creates an identity, a request grants access to a system once the line manager and the system owner have approved it, a move removes what the old role no longer needs, and a leaver event revokes everything and reclaims the licenses. The four sequence templates are those events; the two beside them draw the same loop as an ISO 27001 control and for a single dataset.
- User provisioning process flowchart (joiner, mover, leaver)
User provisioning process flowchart: HR event, identity created in the directory, credentials and MFA, role entitlement bundle, owner approval for privileged access, downstream accounts, verification and recertification.
- Access request process flowchart
Access request process flowchart: role-based request, line manager and system owner approval, segregation of duties check, provisioning and recertification.
- Employee access request process flowchart (joiner and mover)
Employee access request process flowchart for joiners and movers: HR-triggered request, role access profile, manager and owner approval, old-role removal.
- User access removal process flowchart (deprovisioning)
User access removal process flowchart: leaver and role-change triggers, immediate revocation branch, shared accounts, licence reclaim and audit evidence.
Also part of this family
- Data access request process flowchart (request to revocation) — Data access request process flowchart: state the purpose, read the dataset's classification, let the data owner decide, run the personal-data checks, grant time-boxed access, then recertify or revoke.
How the processes connect
All Data management & governance templates
Data governance
- Data governance process flowchart (issue to closure) — Data governance process template for scoping issues, assigning ownership, assessing cross-domain impact, recording decisions, implementing actions and closing with evidence.
- Data governance operating model template — Data governance operating model template for defining the mandate, domains, decision rights, stewardship roles, forums, rollout plan, measures and periodic review.
- Data quality management process flowchart — Data quality management process template for prioritizing critical data, defining measurable rules, monitoring results and sustaining preventive improvements over time.
- Data catalog process flowchart (register to certify) — Data catalog process template for registering an asset, enriching metadata, assigning stewardship, validating user context, certifying status and maintaining the record.
- Data lineage documentation process flowchart — Data lineage documentation process template for scoping an output, tracing source dependencies, mapping transformations, validating evidence and maintaining changes.
- Data lifecycle management process flowchart — Data lifecycle management template covering acquisition, validation, classification, storage, use, sharing approval, retention, legal holds, archiving and evidenced disposal.
Data quality and master data
- Data quality issue management process flowchart — Data quality issue management template for reporting one defect, assessing impact, containing use, confirming cause, remediating data and closing with evidence.
- Master data management process flowchart — Master data management process template for validating requests, matching records, approving changes, publishing identifiers, maintaining attributes and retiring records.
- Business glossary process flowchart (proposal to published term) — Business glossary process template for proposing terms, drafting definitions, resolving duplicates, steward and owner approval, catalog publication, review, revision and retirement.
Data engineering and migration
- Data pipeline development process flowchart — Data pipeline development template for contract design, versioned build, replay testing, security review, data-quality gates, deployment, monitoring and failure handoff.
AI governance
- AI governance process flowchart (inventory to retirement) — Policy-neutral AI governance process template for inventory, risk tiering, control selection, independent review, deployment decisions, monitoring, reassessment and retirement.
- AI use case approval process flowchart — AI use case approval template for single-use-case intake, value, data, feasibility and risk review, conditional approval, recorded decisions and delivery handoff.
Access governance
- Data access request process flowchart (request to revocation) — Data access request process flowchart: state the purpose, read the dataset's classification, let the data owner decide, run the personal-data checks, grant time-boxed access, then recertify or revoke.
Digital transformation
- Data migration process flowchart (assessment to cutover) — Data migration process template for scope assessment, field mapping, cleansing, mock loads, reconciliation, business validation, cutover checks and controlled rollback.
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