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Analytics and data science

In the big data era, more business decisions are being made through data-driven processes than ever before. Investigative analytics and machine learning can provide objective statistical insights that lead to better decisions, adding value.

Data scientists & analysts are often not permitted access to the data they need to produce accurate statistical insights, due to legitimate privacy concerns. Companies need to open up that restricted data, safely.

Privitar products give companies the ability to innovate using data while maintaining an uncompromising approach to data privacy:

  • 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
  • Develop new data products

General Data Protection Regulation

The General Data Protection Regulation (GDPR) will come into force on the 25th May 2018 and will have wide reaching consequences for all companies which control or process personal data of those in the EU. With fines of up to 4% of global revenue, GDPR compliance has become a boardroom issue.

GDPR requires significant changes, some, such as hiring a Data Protection Officer, are relatively straight forward. Others such as Privacy-by-Design, require fundamental changes.

For most businesses, the first step will be to understand what data they currently control and process, what their basis for processing is, what their privacy policies are and what they want to do in the future. This will allow organisations to see where their gaps are and put a plan in place for achieving compliance.

Privitar recommends embedding privacy into the DNA of the business, by focusing on the underlying principals of GDPR and Privacy-by-Design, such as fairness, transparency and data minimisation. By thinking about privacy in existing and new processes companies can ensure they can protect data and provide evidence if anything goes wrong.

Privitar can help organisations evaluate their privacy policies and provide the tools to exceed compliance, with information and auditable pseudonymisation and anonymisation technologies.

  • Ensure compliance with regulation
  • Protect privacy while maintaining the utility of the data

Key use cases include:

  • Value from new data: Turn latent data into valuable analytics and actionable insights.
  • Flexible workflow options: Whether you want quick access to insights or the flexibility to run custom machine learning code, Publisher or Lens supports your workflow.
  • Preservation of privacy: Avoid the privacy risks of providing access to re-identifiable row-level data.
  • Transparency and control: The data holder can view and modify the privacy controls around their data.


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

Download White Paper


Managing privacy risk in advanced analytics and machine learning

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

Download Webinar


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


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


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


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?

Please contact us for further details