Ensure privacy is intrinsic to advanced analytics and data science

Privitar products allow organisations to analyse datasets containing sensitive information (e.g. customer data, employee records, banking transactions, trade data) while preserving privacy or confidentiality. This opens up data for safe secondary use while ensuring consistent and accountable protection of private information.

Privitar offers three ways to protect sensitive data:



Privitar Publisher

Privitar Publisher is a software application which anonymises sensitive data and creates a safe copy suitable for system development and testing, analytics, data science and machine learning, sharing with third parties and processing in cloud environments. Privitar Publisher unlocks this sensitive data for safe use, by removing the identifying information while preserving the valuable patterns and relationships in the large scale data. 

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Privitar Lens

Privitar Lens is a privacy-preserving query interface well suited for statistical analysis of sensitive datasets. Privitar Lens allows rich analytical queries but prevents direct access to the underlying sensitive data. Privacy controls are dynamically applied to each query submitted. This approach supports privacy-preserving analysis of high-dimensional or longitudinal datasets which cannot be protected by data publishing techniques.

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Privitar SecureLink

SecureLink is a data de-identification system that can be used by organisations to overcome trust barriers and combat data siloing. It allows a central organisation, generally a third-party data processor, to join data from many contributing organisations such that the data is de-identified and the central organisation cannot recover the identifiers.

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Essential to modern data architectures

Like security, privacy protection should be designed into data systems at every level, not bolted on as an afterthought. Privitar products add foundational privacy to your data processing architecture at every stage: ingest, data preparation, analytics, statistical modelling and reporting.

  • Integrate with and execute within your Hadoop environment and scale to big data, so there is no need to take data out of its secure environment
  • Bring consistency, auditability and accountability to the protection of sensitive data, through the use of centrally managed Privacy Policies
  • Integrate with metadata stores both to identify sensitive data and to record how risks have been mitigated
  • Record full data lineage of anonymised and shared data


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

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