Data Science · Beginner level

Beginner level · Module 5 of 5 · 10 guided hours

Data Privacy and Ethics in Analysis

Protect the people behind the data when analysing, publishing and sharing results.

Learning objectives

  • Identify personal and sensitive data
  • Apply anonymisation and safe-output techniques
  • Share data and results responsibly

Topics

  • personal and sensitive data
  • direct and indirect identifiers
  • pseudonymisation and anonymisation
  • small-cell suppression
  • consent and purpose
  • safe data sharing

Lessons

  1. Lesson 1 Personal Data and Identifiers

    Recognise data that can identify people, directly or by combination, and why it must be protected.

    personal datadirect identifierindirect identifiersensitive data

  2. Lesson 2 Anonymising and Protecting Outputs

    Remove or reduce identifying information in data and results before sharing.

    pseudonymisationgeneralisationsmall-cell suppressionre-identification risk

  3. Lesson 3 Consent, Purpose and Responsible Sharing

    Use data only for agreed purposes, share it safely and follow your organisation's policies.

    informed consentpurpose limitationdata sharing agreementsecure transfer

Practical activity

Prepare a shareable version of the water survey and its tables: remove identifiers, aggregate small groups and write a data sharing note.

Expected outcomes

  • Privacy-protecting outputs
  • Responsible data handling habits

Assessment

The level project assessed against its criteria, including a privacy review of all outputs.

Free taster lesson Data Privacy & Security in Analytics Read a free self-study lesson on this topic in the Free Course Library.

Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.