The next generation of de-identification software. Privacy Analytics Eclipse is the world’s only software that de-identifies structured data using a proven, risk-based method. Built using Apache Spark, Privacy Analytics Eclipse is able to manage Big Data for healthcare unlike ever before. Turn your organization’s vast stores of PHI into high quality, HIPAA-compliant de-identified data with the lowest risk of re-identification.
Limit the Risks, not the Rewards when Enabling Big Data Analytics for your Organization
Privacy Analytics Eclipse can de-identify structured data from a variety of sources.
It can be used to de-identify billions of records concurrently.
From large data warehouses to smaller datasets, Privacy Analytics Eclipse can manage many data concerns.
The data is entered via CSV files or Oracle/SQL server.
Privacy Analytics Eclipse looks at the risks contained in the data, the context for release, and the controls in place to apply the right level of de-identification.
Automate Your De-identification Process
The value and risk of big data in healthcare and other industries only increases as it is linked to create longitudinal patient records from which various insights can be derived. Privacy Analytics Eclipse is a solution that balances the privacy and the business requirements that are driving new applications for healthcare analytics. Ensure your organization is relying on de-identification techniques that not only unlock sensitive data but enforce your brand as a trusted player in the emerging data economy.WATCH THE OVERVIEW
“Privacy Analytics Eclipse provides a sound evidentiary basis for substantiating the claim that personal information is de-identified. It also allows for appropriate security safeguards to protect the data based on an empirically assessed risk of re-identification in the recipient environment.”- Anita Fineberg, LL.B., CIPP/C, Privacy Lawyer and Consultant
Transform Your Data
Architected on Apache Spark, Privacy Analytics Eclipse is built for scalability, flexibility and overall power. Using this software allows users to:
- Apply sophisticated de-identification techniques to transform the data in a way that will meet an established privacy risk threshold
- Retain analytic value in the data by creating groupings of dates with the ability to preserve precise intervals and sequence information or retain dates within a specified window of time to ensure valid results
- Support time series analytics by creating longitudinal patient records that preserves data formatting and ensures repeatable masking over time
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