Pryv.io Personal Data Mapping to enable automatic integration with existing warehouses

Bridging the gap for privacy compliance and managing data-subject requests on personal data access and processing

Pryv.io Personal Data Mapping to enable automatic integration with existing warehouses.

Integrate existing data warehouses with Pryv.io privacy back-end:

  • Make legacy systems (warehouses) easy to integrate with new external systems within a privacy-compliant environment. 
  • Significantly reduce time and errors managing data-subject requests.

Pryv developed and commercialized a privacy-by-design middleware system that provides full, innovative personal data life cycle management. This technology allows for privacy compliance, interoperability and data sharing to a granular-level, using transparent, unambiguous enforcement of consent applied on a data set.

Pryv.io Data Mapping provides companies with existing data warehouses the means to adopt faster innovation, integrate real-world personal data and build better personalised services, all within a transparent and privacy-compliant environment. 

Existing systems usually face major hurdles integrating with external solutions with the synchronisation of very big datasets and the transfer and storage of multiple copies of sensitive data. Pryv.io Data Mapping allows:

  • to benefit from the capacity of privacy-by-design models;
  • map dynamically existing datasets in a transparent and unambiguous form, presented to an individual for his enlightened consent;
  • unlock the capacity to offer privacy on legacy datasets.  

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Current status for managing data-subject requests on personal data access and processing by systems without privacy-by-design architecture:

Today, initiating a NEW data processing in organizations with legacy systems involves time consuming processing for the Data Protection Officer (DPO) to scope the necessary datasets, collect consents and verify compliance with applicable regulations. Furthermore, it requires manual intervention of technicians to extract datasets. Multi-employees interaction and manual processes are prolonged, lack efficiency and generate errors. Such processes would not be acceptable in the short-mid term. Investments in innovation and automation must be considered. (Pic. 1)

Data Mapping Pryv Consent Privacy 1
Pic.1: Managing data-subject requests on personal data access and processing by systems without privacy-by-design architecture:

Managing data-subject requests on personal data access and processing by implementing Privacy-by-design solutions 

Privacy-by-design solutions digitalize consent collection and offer effective control over the personal data life cycle. Pryv.io provides a privacy-by-design framework to interact with personal data. This framework only operates on data it controls. (Pic.2) Still, this solution requires the data to be fully copied and synchronized from/with the legacy system. This process is not optimal for large data warehouses, data lakes and highly dynamic data sets.

Data Mapping Pryv Consent Privacy 2
Data Mapping Pryv Consent Privacy 2

Pic.2 Managing data-subject requests on personal data access and processing by implementing Privacy-by-design solutions

Solution: Personal Data Mapping to enable automatic integration with existing warehouse for managing data-subject requests on personal data access and processing

To meet the needs of mapping large data warehouses, data lakes and highly dynamic data sets, Pryv has developed a new technology that maps dynamically existing datasets in a transparent and unambiguous form to be presented to an individual for his enlightened consent.  

“Unlocking the capacity to offer privacy on legacy datasets allows us to provide our services to a much broader set of companies handling personal data, which is important since the older ones are more in need of an up-to-date system regarding privacy regulations.” says Pierre-Mikael Legris, CEO and co-founder of Pryv SA.

Privacy-by-design solutions digitalize consent collection and offer effective control over personal data life cycle. Pryv.io provides a privacy-by-design framework to interact with personal data. To operate, this framework must stand as a “gateway” to interact with personal data. Including Dynamic Mapping. On Existing Datasets allows to benefit from privacy by design for new over existing data sets. (Pic.3)

Data Mapping Pryv Consent Privacy 3

Pic.3 Personal Data Mapping to enable automatic integration with existing warehouse for managing data-subject requests on personal data access and processing

To learn more about how Pryv.io Dynamic Data Mapping will resolve your personal data management needs and facilitate automatic integration of personal data mapping with your existing warehouses contact us at: business@pryv.com

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