Privacy Glossary

Making sense of the jargon behind data protection

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Privacy Empowers Businesses

Discover how with our webinars, white papers, and other resources

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IN:CONFIDENCE 2018

CELEBRATING THE POWER OF RICH, USEFUL AND SAFE DATA

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Data Governance and GDPR

How to ensure compliance for data analytics platforms

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Pharmaceuticals

Share and analyse health care data without revealing the identity of your patients:

Ensure the anonymity of underlying patient records and go beyond traditional de-identification methods.

Transform and anonymise sensitive data to facilitate secondary use:

Transform your data using sophisticated masking and anonymisation technique and make it suitable for use in broader contexts.

Key use cases include:

- Pooling of statistics across providers
- Safe sharing of data with researchers

Financial Services

Ensure compliance with regulatory requirements:

Mask or anonymise sensitive data appropriate to regions or departments without a significant impact to data utility and ensure compliance with data protection legislation.

Provide safe access to sensitive data sets to both internal users and third parties for further analysis:

Privitar enables collaboration between institutions on sensitive data sets for testing or analysis.

Key use cases include:

- Customer analytics and marketing
- System testing on real datasets without re-identification risk
- Safe sharing of datasets for technology and business innovation
- Anonymisation of data suitable for cloud processing

Telecommunications

Protect against the unintended consequences of re-identification attacks or the mosaic effect:

Privitar ensures that risk metrics are constantly re-evaluated as new data sources are added and joined for profiling purposes.

Mine behavioral analytics from this highly personal and pervasive data class:

Privitar ensures that privacy is considered at the outset and in depth with sound privacy-by-design principles.

Key use cases include:

- Operational monitoring and optimisation
- Customer retention and marketing
- Creation of data products based on location and activity data for an anonymised populations

Retail

Protect your consumers personal information in compliance with regulation.

Mine consumer data, demographic information for insights and predictive analytics: Privitar ensures data anonymity and enables safe broader access

Key use cases include:

- Customer analytics and marketing
- Safe sharing of data with external parties

Risk & compliance

Ensure compliance with regulation (e.g. GDPR)
Enable safe public cloud adoption
Protect against data breach and the misuse of data

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Insights

Analyse sensitive operational data to gain cost efficiencies or competitive insight
Safely open up restricted data for more comprehensive analysis
Provide benchmark and consensus views without revealing proprietary information

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Sharing & collaboration

Transfer sensitive data across borders
Share anonymised data with partners and academics
Collect and analyse data without revealing sensitive attributes
Generate representative data for testing

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CIOs

Have a clear view of what sensitive data the organisation holds, what policies are in place to mitigate privacy risks, and full audit and data lineage of each safe data product.

CDOs

Define robust privacy policies, and drive the transformation of sensitive data sets into safe data products, bringing consistency and full accountability to the governance of confidential data.

Analysts and data scientists

Use Privitar products to access data safely, and to understand and control how best to apply Privitar’s statistical anonymisation techniques to maximise data utility.

Legal & compliance

Have confidence that you and your teams are meeting and exceeding compliance regulation.

Data engineers

Build privacy protection into the data platform by integrating Privitar into each stage of the data pipeline, orchestrating policy execution through API integration.