Insights & analytics with third parties - Sharing a safe copy of data

Organisations and governments are increasingly recognising the value in combining fragmented datasets across multiple verticals. This might include sharing sensitive data to enable innovative partnerships, with academic institutions for research purposes, or with consultancies for better advice, analysis and change management. But companies are frequently prevented from leveraging the skills and expertise of third parties due to concerns over sharing data.

Privacy preserving technology can reduce the risk of sharing data externally allowing companies to:

  • Transfer sensitive data across borders
  • Share anonymised data with partners and academics


Key use cases include:

  • Enable co-operation with others without relying solely on trust, including competitors.
  • Carry out analysis across a group of industry peers who compete, without jeopardising the privacy of customers.
  • Compare industry data without putting the data owners at risk.

Safe data use for development and test systems

Most development organisations complain about the lack of high quality test data. The time that is spent on acquiring, validating, organising, and protecting test data has a significant impact on the performance and effectiveness of teams.

Privacy engineering techniques, allow you to anonymise sensitive data and create safe copies for analytics, development and test, whilst preserving useful patterns in data.

  • Collect and analyse data without revealing sensitive attributes
  • Generate representative data for testing

Key benefits include:

  • More robust. By testing by using a safe copy of production data, rather than synthetic data.
  • Reduced exposure to data breaches by reducing the number of individuals and environments with access to sensitive data
  • Faster innovation. Removing the barriers for development and test teams means they can test, iterate and deliver faster.

Resources:

Key GDPR directives and implications explained in this concise guide compiled by Privitar and NTT DATA

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Download the Privitar guide to delivering big data analytics under GDPR

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Privitar Provides Products to Meet Data Privacy by Design Requirements of GDPR

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A Cloudera and Privitar joint webinar: Data Privacy - enabling compliant and innovative data science

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Testimonials

Companies may be unknowingly and unwillingly leaking sensitive information in non-obvious ways as the use of data for secondary purposes expands. Privitar is providing products that integrate neatly with Cloudera Enterprise, the leading open source data management platform based on Apache Hadoop.

Tim Stevens, VP Corporate and Business Development, Cloudera

Privacy matters: One solution, on the privacy side at least, is to separate the identity of the person being measured by a sensor from the data they generate. John Taysom, a fellow of the University of Cambridge and co-founder of privacy company Privitar, believes this “disassociation” is key because companies and governments get the data without a risk to privacy.

Sean Hargrave, The Guardian

It is essential that we develop practical ways of protecting privacy, otherwise we may not be able to sustain growth in the internet based economy.

David Cleevely CBE, FREng:
Chairman Centre for Science & Policy, University of Cambridge

Privacy is a game changer; it will be to organizations in 2016 what websites were to companies in 2000. So this is the year to up the ante on your investments: you need the right cross-functional team, good governance practices, and the technical tools to ensure that all of your systems are in compliance with both laws and internal privacy guidelines. Making the right investments will let your firm drive business growth, win new customers, and build deeper customer relationships.

Forrester Research, Jan ‘16

Privitar is working with some of the world’s largest companies across industries

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

Want to know more?

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