Datalake Data Governance personas for airline

For an airline business, implementing a Data Lake Governance Framework requires defining clear roles (personas) to manage the data lifecycle, ensure compliance, and enable trusted analytics. Below are the key personas needed—tailored for the aviation context, which involves complex regulatory, operational, and customer data:





🔵 1. 

Chief Data Officer (CDO)



Responsibility: Strategic leadership over data governance.

Focus Areas:


  • Align data initiatives with business goals (e.g., fuel optimization, customer experience).
  • Ensure compliance with regulations (GDPR, FAA, IATA, etc.).
  • Drive culture around data literacy and stewardship.






🔵 2. 

Data Governance Lead / Program Manager



Responsibility: Operational ownership of the data governance program.

Focus Areas:


  • Define governance policies and standards.
  • Coordinate stakeholders (IT, legal, operations, marketing, etc.).
  • Implement data quality and classification initiatives.






🔵 3. 

Data Steward(s)



Responsibility: Ensure data quality, lineage, and definitions are maintained.

Types:


  • Flight Operations Steward (e.g., aircraft telemetry, maintenance logs)
  • Customer Experience Steward (e.g., loyalty data, NPS, booking behavior)
  • Finance Steward (e.g., fare classes, revenue reports)



Focus Areas:


  • Metadata management.
  • Business glossary ownership.
  • Data issue resolution.






🔵 4. 

Data Owner(s)



Responsibility: Accountability for specific data domains.

Focus Areas:


  • Approve access policies.
  • Define data access rights and sharing agreements.
  • Ensure accuracy and completeness in their domain.



Examples:


  • Airport Operations Data Owner
  • Revenue Management Data Owner
  • Crew Scheduling Data Owner






🔵 5. 

Data Architect



Responsibility: Define the structure and integration approach of the data lake.

Focus Areas:


  • Data modeling and zone definitions (raw, curated, trusted).
  • Data cataloging and lineage architecture.
  • Support for schema evolution.






🔵 6. 

Data Engineer



Responsibility: Build ingestion, ETL/ELT, and transformation pipelines.

Focus Areas:


  • Automate data ingestion from aircraft sensors, check-in systems, weather APIs, etc.
  • Create and maintain data lake zones.
  • Ensure data observability and quality checks are in place.






🔵 7. 

Security and Compliance Officer



Responsibility: Ensure data usage complies with regulations and internal policies.

Focus Areas:


  • Data encryption, masking, and retention policies.
  • Regulatory compliance (GDPR, PNRGOV, TSA, etc.).
  • Access control and audit logging.






🔵 8. 

Data Consumer / Analyst / Scientist



Responsibility: Use governed data for analytics, prediction, and reporting.

Focus Areas:


  • Understand data context via metadata and catalog.
  • Provide feedback on data quality or accessibility.
  • Use curated zones for AI/ML models (e.g., predictive maintenance, delay prediction).






🔵 9. 

BI / Reporting Lead



Responsibility: Ensure reports use governed, trusted data.

Focus Areas:


  • Connect dashboards to curated/semantic layers.
  • Monitor KPI accuracy (e.g., on-time performance, baggage claim SLAs).
  • Promote governed self-service analytics.






Optional (Context-Dependent) Personas:



  • Legal/Privacy Officer – For data sharing across borders and passenger privacy.
  • Vendor/Data Partner Manager – For data-sharing agreements (e.g., codeshare partners, airport authorities).
  • ML Ops/AI Governance Specialist – If using AI models with sensitive or operational data.





Would you like this framework mapped to data lake layers/zones or cloud-native tools (like Azure Purview, AWS Lake Formation, etc.)?


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