Oka-Bi Pseudonymisation Toolkit is a privacy-enabled data warehouse automation product, which was our 1st product release.
Licensed by 8 public sector healthcare and life sciences organisations, this product enables our customers to implement proactive and reactive data privacy measures in an integrated data warehouse, which is fully metadata driven.
Many of these features are now migrated to StakGen.io, but this is a compelling automation platform which can be deployed in SQL Server On-Premise or IAAS cloud environments to safeguard and integrate personal and non-personal data from a variety of heterogeneous sources.
The following recommendation is from one of our customers, NIHR Imperial College, Biomedical Research Centre.
"We chose the Oka-Bi Pseudonymisation Toolkit for our Translational Research in Pulmonary Hypertension at Imperial College (TRIPHIC) programme because it combined the stringent protection of patient information with a flexible and scalable approach to handling data from diverse sources. With the support of Oka-Bi, we have been able to develop a robust system that links together clinical datasets, helps manage the associated biological samples in our Bio-repository and makes pseudonymised information available for research purposes. Oka-Bi enabled us to be self-reliant and remain fully in control of the data, which is stored and processed within our infrastructure."
Professor Martin Wilkins, Director of NIHR/Wellcome Trust-Imperial Clinical Research Facility at Hammersmith Hospital
Practical Pseudonymisation (EHI Live - NEC Birmingham - 2011)
Oka-Bi's David Hill on "Practical Pseudonymisation" EHI Live 2011
This video, from the Oka-Bi vaults, is from e-Health Insider Live 2011 and demonstrates the commitment we have at Oka-Bi with regards to socialisation and evangelism of data privacy concerns.
We firmly believe in the power of automation to support business critical data governance and privacy processes, and consistent delivery of architectures, standards and coding patterns that are "baked in" to the original design of a data warehouse ecosystem.