Why Anonymize Data?
Data anonymization serves two key purposes:
- Privacy Protection: Anonymizing data ensures that individual identities cannot be directly linked to specific records. Participants’ privacy is safeguarded.
- Ethical Use: By anonymizing data, we minimize the risk of unintended consequences or misuse. It aligns with our commitment to ethical practices.
Our Approach to Data Anonymization
1. Removing Identifiers:
- We remove or encrypt direct identifiers (e.g., names, email addresses, social security numbers) from assessment data.
- Pseudonyms or unique codes are used instead.
2. Aggregation and Generalization:
- Aggregating data across participants helps prevent re-identification.
- Generalizing attributes (e.g., age groups, job roles) further anonymizes data.
3. Noise Injection:
- We add random noise to numerical data (e.g., test scores) to prevent precise identification.
- Statistical techniques ensure data quality despite noise.
4. Data Retention Policies:
- We retain anonymized data only for necessary periods.
- Regular reviews determine data retention timelines.
Transparency and User Consent
We inform participants about our anonymization practices during data collection. Informed consent includes details about how their data will be handled.
Reporting Concerns
If you have any questions or concerns related to data anonymization, please reach out to our data privacy team at hi@dqmetrics.com.