Ownership And Steward Roles

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Why this matters

As a Data Architect, you do not just design systems—you design accountability. Clear ownership and steward roles ensure data is trusted, secure, and change-managed. Without them, access approvals stall, quality issues linger, and compliance gaps appear.

• Real task: Define who approves access to Finance data and under what conditions.
• Real task: Assign a steward to monitor SLA for Product data quality and escalate incidents.
• Real task: Document RACI for schema changes to Customer Master and wire it into the catalog/workflows.

Concept explained simply

Ownership answers “Who is accountable for this data?” Stewardship answers “Who makes sure it’s healthy day to day?” Custodians run the infrastructure. Producers create data; consumers use it. Governance defines rules, but owners and stewards make those rules real for each dataset or domain.

Mental model

Think of each important dataset as a product:

• Owner = Product Manager (accountable decisions)
• Steward (Business) = Service Manager for meaning/quality/usage
• Steward (Technical) = Service Manager for metadata/lineage/controls
• Custodian = Platform/DB admin (implements controls, backups, access)
• Producer = Team emitting the data
• Consumer = Teams relying on the data

Use RACI to make responsibilities explicit: Responsible (does the work), Accountable (final decision), Consulted (inputs), Informed (kept in the loop).

Core roles and responsibilities

Data Owner

• Accountable for data purpose, risk, and policy compliance.
• Approves access and sensitive use cases (or delegates policies).
• Prioritizes data quality fixes; sets SLAs and acceptance criteria.
• Approves schema-breaking changes and retention/classification rules.

Data Steward (Business)

• Maintains business definitions, glossary, and data usage guidelines.
• Monitors data quality KPIs; triages issues; coordinates fixes.
• Validates classification/PII tags; supports audits.

Data Steward (Technical)

• Maintains metadata, lineage, and data contracts.
• Ensures controls (access policies, encryption states) are implemented.
• Coordinates with producers/custodians for change management.

Custodian (Platform/DB Admin)

• Implements access grants/ revokes; backups; DR; performance.
• Executes technical controls approved by owner/stewards.

Producer

• Builds and maintains pipelines feeding the dataset.
• Fixes upstream issues causing breaks in SLAs or quality.

Consumer

• Requests access; follows usage policies; reports issues.

Governance Lead / Committee

• Sets organization-wide policy, minimum controls, escalation paths.
• Resolves cross-domain conflicts; reviews exceptions.

Setting up ownership and stewardship in your org (step-by-step)

1. List your critical domains and datasets (e.g., Customer, Orders, Finance, Product).
2. Assign a named Data Owner per domain/dataset (one accountable person).
3. Assign Business and Technical Stewards; define time commitment (e.g., 10% FTE).
4. Define RACI for key activities: access, quality, schema changes, classification, retention, incident comms.
5. Publish roles, contacts, SLAs, and workflows in your data catalog.
6. Implement request workflows (e.g., access) that reference Owner/Steward decisions.
7. Create review cadence (monthly quality review; quarterly role validation).

Worked examples

Example 1: Access request to Finance Revenue table

Scenario: A marketing analyst requests access to the Revenue table.

• Owner: Reviews business justification, approves/denies access or sets conditions (read-only, masked columns).
• Business Steward: Confirms sensitivity classification; updates catalog with usage notes.
• Technical Steward: Ensures policy tags/column masking are set.
• Custodian: Applies grant and masking; logs action.
• Consumer: Accepts usage terms.

Example 2: Schema change in Customer Master

Scenario: Add new column customer_segment; deprecate legacy flag.

• Producer: Proposes change with impact analysis.
• Technical Steward: Verifies lineage/impacted downstream datasets; updates contract.
• Business Steward: Ensures glossary definition and value list are clear.
• Owner: Approves the change and deprecation timeline.
• Custodian: Implements DDL in prod following release process.
• Consumers: Informed with migration guidance.

Example 3: Data quality incident on Orders

Scenario: 8% nulls in order_total exceed SLA.

• Business Steward: Opens incident, prioritizes severity, communicates blast radius.
• Producer: Fixes upstream transformation, backfills data.
• Technical Steward: Verifies fix, updates monitoring rule.
• Owner: Confirms resolution meets SLA; approves post-incident actions.

Templates you can copy

Minimal RACI activities

• Access approval: A=Owner, R=Custodian, C=Stewards, I=Security
• Data quality triage: A=Owner, R=Business Steward, C=Producer/Tech Steward, I=Consumers
• Schema-breaking changes: A=Owner, R=Tech Steward/Producer, C=Business Steward, I=Consumers
• Classification/PII tagging: A=Owner, R=Business Steward, C=Privacy, I=Custodian
• Incident comms: A=Owner, R=Business Steward, C=Tech Steward, I=Stakeholders

Exercises

These mirror the graded exercises below. Do them here, then submit your answers in the exercises section.

Exercise 1: Draft a RACI for a critical dataset

1. Pick a dataset (e.g., Customer Master).
2. Define R, A, C, I for: access, quality, schema changes, classification, incident comms.
3. Write 3–5 sentences explaining your choices.

Exercise 2: Design an access workflow

1. Describe steps from request to grant/reject.
2. Include decision criteria (role, purpose, data sensitivity).
3. Set an SLA and escalation path.

Before you move on — checklist

• I can name the Owner and Stewards for at least one dataset.
• I can explain the difference between Owner, Steward, Custodian, Producer, Consumer.
• I can draft a RACI for 5 key activities.
• I know the access approval workflow and its SLA.

Common mistakes and how to self-check

• Mistake: Two “co-owners.” Fix: Pick one accountable Owner; others can be Consulted.
• Mistake: Stewards named but not empowered. Fix: Document authority (approve glossary changes, open incidents, request fixes).
• Mistake: RACI too generic. Fix: Tailor per dataset; specify tools and SLAs.
• Mistake: No communication plan for breaking changes. Fix: Define notice periods and migration guidance.
• Mistake: Access approvals pile up. Fix: Use policy-based approvals for low-risk roles; escalate after SLA breach.

Practical projects

• Project A: Assign Owner/Stewards for two domains and publish in your catalog with contacts and SLAs.
• Project B: Implement a data quality dashboard with 3 KPIs owned by the Business Steward.
• Project C: Document and test an end-to-end access workflow including masking for sensitive columns.

Who this is for

• Data Architects defining governance for data platforms.
• Data Engineers and Analytics Engineers integrating policies into pipelines.
• Domain leaders taking accountability for data products.

Prerequisites

• Basic understanding of your data domains and critical datasets.
• Familiarity with data catalogs, access controls, and incident management concepts.

Learning path

1. Learn data domains and critical datasets.
2. Assign Owner and Stewards; define RACI.
3. Implement access and change workflows with SLAs.
4. Set up quality monitoring and incident handling.
5. Review roles quarterly and iterate.

Mini challenge

Pick a dataset with recent issues (e.g., delayed updates). Propose role assignments, a RACI for quality triage, and a simple SLA (e.g., daily by 7 AM UTC). Write a one-paragraph communication you would send to consumers when incidents occur.

Next steps

• Finish the exercises and take the quick test to validate understanding.
• Apply the RACI template to one live dataset this week.
• Schedule a monthly review with Owners and Stewards.