Unlocking the Value of Healthcare Data with SAP HANA Data Anonymization
We live in an age where data has become new digital currency and organizations are looking into ways to unlock the value of their data, but often fear prevents them to do so. On the other hand, nobody wants to be the next to suffer data breach by exposing sensitive customer data. The paradox remains – how to unlock valuable insights from data without compromising on the privacy of the individuals.
Modern, intelligent enterprises are using data anonymization to overcome these challenges and continue to provide their business users with relevant, timely, and actionable insight without exposing their users to potentially sensitive information. Data anonymization, also known as de-identification, it is a structured approach to protect the privacy of individuals whilst enabling analytics on complex data sets. This is a game-changer in the highly regulated healthcare industry because previously un-mineable data can now be safely used to create insights that can save lives. For instance, data such as mental health records can be safely anonymized, while still producing actionable data models around suicide prevention.
HarrisLogic, a technology and clinical services company, emphazises that data sharing across the industry is beneficial for everyone, however the inability to anonymize often stymies research into cross-industry data silos. As a consequence, poor coordination leads to fewer outpatient appointments, lower adherence to treatment plans, system-wide inefficiencies, and increased readmissions. Hudson Harris, the chief engagement officer at HarrisLogic, says, “The ability to protect data and create insights will add not only value, but draw customers looking to embrace privacy by design.”
The latest release of SAP HANA reflects SAP’s deep research into effective privacy techniques by automating the complex computations necessary to carry them out. While several techniques already familiar to data scientists, such as randomization and permutation have proven insufficient to anonymize data completely, SAP’s sets a new bar for in-database anonymization as well as SAP HANA’s built-in Predictive and Machine Learning capabilities. Using k-anonymity, SAP HANA aggregates indirect identifier values to make an individual indistinguishable within a group of at least k members. Even with all fields exposed, you cannot identify a single person, rather, you can identify only k people, essentially hiding individuals in herd privacy.
In addition to this, the differential privacy feature goes even further to protect individual identities by adding random noise to sensitive numerical values. This data noise is designed in such a way that the noise elements in each value statistically cancel each other out in large data sets. This means you can disconnect individual identities from the values for general use, but maintain the statistical significance of advanced analytics.
With SAP HANA Data Anonymization, healthcare customers can effortlessly anonymize sensitive and confidential data in real time and gain analytical insights from it without compromising data security or personal privacy.
By changing the way we see data and the risks associated with viewing sensitive information, we open new paths to research and ultimately, better care. In addition to these organizational benefits, this unlocks the ability for deeper collaboration among healthcare providers. While no one can guarantee that a data breach will never occur, SAP HANA Data Anonymization is a powerful tool for healthcare and non-healthcare organizations. Data anonymization methods such as k-anonymity and differential privacy have the potential to unlock a tremendous value and contribute to higher level of care. While this is one scenario, it illustrates the applicability and impact SAP HANA Data Anonymization has for better analytical results on sensitive data regardless of industry. Innovate with confidence on SAP HANA.
-> HarrisLogic is an SAP Innovation Award Winner! Learn more about their story here: http://ow.ly/JsVh30nVYGL
-> To learn more about SAP HANA Data Anonymization, go to http://www.sap.com/data-anonymization
-> For more information, please visit our SAP HANA security website at http://www.sap.com/hanasecurity
Hi Roosi Magi,
thanks for sharing these very interesting facts about k-anonymity and differential privacy.
Thank you Sebastian. With great pleasure!
Thank you so much for sharing such interesting facts..Really found some valuable facts in your posts.Thank you so much
Thank you Tommy for your kind feedback!
This is really nice explanation. Thanks for sharing !!
Anonymization methods available in SAP HANA allow you to gain statistically valid insights from your data while protecting the privacy of individuals.
Thank you Trupti. Glad you enjoy the read.
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