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Data Privacy as a Service

Data-driven decision making is a key competitive factor for modern businesses. Enterprises adopt Data as a Service to pool datasets from previously siloed data stores. This enables data provisioning, processing and compliance on one central data hub.

However, adopting Data as a Service and the added complexity of managing high data volume and variety comes with challenges such as maintaining privacy for datasets, data policy and compliance and increases the risk of malicious or accidental data breaches from internal actors.


Privacy Policy Management and Compliance

When managing large data volumes, complexity in maintaining compliance and setting policies increases. Privitar tools help set consistent privacy policies across the data estate and introduce additional features such as watermarks which facilitate data lineage and audits.


Minimising Risk of Data Breaches

Making data widely accessible across an organisation can increase risk of malicious or accidental data breaches by internal actors. In particular, in some cases anonymised data may be re-identified by linking seemingly anonymised datasets together. We introduced features such as Protected Data Domains that minimise the risk of such linkage attacks.


Dpaas Stack

Data Workflow Architecture

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Key Features

Publisher for Privacy as a Service

  • De-identify sensitive data with masking, perturbation or generalisation techniques
  • Preserve useful patterns in data and retain referential integrity
  • Embed watermarks in datasets to facilitate auditing and data lineage
  • Automate privacy policy creation and centrally manage policies consistently across datasets in the enterprise
  • Retain customer data format, e.g. email addresses can be represented in email form


Solution brief: Data Privacy as a Service

Reduce the time, cost and risk of provisioning valuable datasets.

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Webinar - Data de-identification 101

Strategy, techniques and considerations

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Data as a Service (DaaS) - Challenges and Solutions

What are some of the challenges of adopting a Data as a Service (DaaS) approach, and how best to overcome them.

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Data Privacy and Innovation for Telecoms

How can telecoms innovate with data whilst ensuring the privacy of their customers' sensitive information?

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