Privacy, Governance, and Ethical Practice

What is data governance?

Data governance defines how data is owned, accessed, described, protected, and used.

Use only what you need

• Data minimisation: collect and analyse only the data needed for the task.
• Role-based access: people see only what their role requires.
• No identifiable records in screenshots, slide decks, or public repositories.
• Approved environments for sensitive data (not personal laptops or public tools).

Privacy and fairness

Removing names isn't always enough. Combinations of fields can re-identify people:

Fairness questions:

• Could the project disadvantage a group?
• Was the data collected appropriately, with proper consent?
• Could the output be misinterpreted or misused?

Relevant regulations (examples):

Requirements differ by jurisdiction and change over time. Follow your organisation's legal and privacy guidance.

Practical safeguards

When the permitted use is unclear, ask the data owner or privacy team.

Key takeaways

• Responsible analytics is part of quality work, not a final checkbox.
• A useful analysis is accurate, appropriately scoped, secure, and honest about its limitations.

Try it: Review a proposed customer analysis and list what personal data is necessary, what can be removed, and who should be allowed to see the results.