Explore Tasks
Design and review governed data-access entitlement policy
Data owners receive an enforceable entitlement policy (roles, approvals, reviews) and review findings.
1job does it
6jobs help with it
45skills it needs
- Data Governance Lead
- Data Steward
- Data Governance Manager
- Head of Data Governance
- Chief Data & AI Officer
- Database Administrator
- Head of Marketing Operations
Does itHelps with it
- Reading and tracing unfamiliar code
- Reviewing human- and AI-generated code changes for correctness and risk
- Sampling and reviewing a team's work against standards
- Diagnosing misleading data visualisations
- Verifying reports and dashboards before and after release
- Verifying AI-assisted outputs against sources
- Disclosing AI contribution to professional work
- Testing competing explanations with discriminating evidence
- Independently checking analytical conclusions and claims
- Escalating unresolved risks with evidence and clear ownership
- Giving specific developmental feedback on data and AI work
- Judging the materiality of defects and deficiencies for the intended use
- Classifying AI uses against regulatory obligations
- Governing shared data definitions
- Enforcing and auditing data access
- Judging whether and how to use AI for a task
- Applying data classification and handling rules
- Assigning and operating data ownership and stewardship
- Designing enforceable data governance policies
- Mapping stakeholders' decisions, constraints and needs
- Working through stakeholder conflict over evidence and responsibility
- Identifying and prioritising critical data elements
- Designing decision rights and dispute routes for data and AI work
- Building data protection by design into data products and pipelines
- Locating and acting on personal data for individual rights requests
- Writing data quality rules
- Recognising personal data and privacy duties
- Assessing privacy risk through data protection impact assessments
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Designing testable data controls
- Controlling disclosure risk in shared data and outputs
- Recognising and containing suspected personal data breaches
- Resolving consent and suppression status across systems
- Mapping personal data processing and flows
- Interpreting policy scope and delegated authority limits
- Building bounded, secure data-service APIs
- Monitoring and testing data control effectiveness
- Designing role-based access entitlement models
- Identifying and quantifying decision downside and exposure
- Making accountable decisions under uncertainty
- Revising prior decisions when evidence changes
- Reasoning about systems, feedback and second-order effects
- Facilitating group decisions using disputed evidence
- Rating risks against appetite and choosing proportionate treatment
- Recognising and resolving ethical conflicts in data and AI work
Paths that teach the skills it needs
Skill Path
Data Literacy for Business Decisions
Judge whether a business claim from a table, KPI, chart or dashboard really holds up.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Privacy, Security and Access for Data and AI
Protect personal data and access with impact assessments and incident evidence.
- Modules
- 5 open
- Practice data
- Raket Parts