Recently, data science and data-driven businesses have been marred by scandal. From the Cambridge Analytica election affair, to Google’s secretive move into the healthcare space, people are angry and regulatory authorities are showing teeth.
However, we believe 2020 will have good things in store for the industry. Namely, we suspect there will be a focus on making data actionable for data science and embedding privacy into innovation.
Data scientists are limited by privacy concerns, but they don’t have to be
A lack of data access is a core problem that data scientists face on a regular basis. When their job is to find actionable insights, traditional approaches to handling privacy makes it challenging to get right. For example, masking and encryption wipe the analytical value of the data, and rob scientists of the material necessary for completing their job. This has pitted compliance and data teams against one another, while leaving both teams unfulfilled. After all these approaches fail to meet the values of either team: they wipe value and don’t ensure personal data is protected.
Yet, both of these objectives are essential to innovation and business growth. Organizations require actionable data and consumer protection. If approached correctly, privacy protection is the method to unlock data. We know, this sounds like an oxymoron. But truthfully, preserving privacy the right way will give your data scientists increased and improved data.
2020 will be the year of risk-aware anonymization
In order to achieve innovation goals, businesses must rethink the way they handle privacy. Organizations cannot rely on traditional methods like access controls, masking, encryption, and tokenization in order to achieve anonymized data. These legacy processes were intended for security, not privacy, and they appeared at a time when data wasn’t valued by organizations in the same way as it is today.
In the new era of anonymization legislation, none of the legacy approaches to privacy compliance are fit for purpose.
The best solution on the market today is risk-aware anonymization: A technique that combines the most advanced privacy approaches – differential privacy, k-anonymity – with AI to optimize for risk reduction and value preservation at scale. By using this tool, analysts and scientists will be able to unlock their data lakes and warehouses while respecting consumer privacy. In essence, the process of stripping personal information will transform consumer data to business IP.
Anonymization makes it possible to embed privacy into innovation
Once businesses have invested in risk-aware anonymization technology, they will be able to reach a new bound of success. Not only will their scientists have full access to data, but consumer privacy will also be ensured.
We predict this is the wave to come next year, in which all business stakeholders will achieve their priorities and boost performance. We believe this is the solution to better organizations through and through, and that it is only by establishing privacy in the business model that innovation can occur.
Privacy is the foundation of progress. 2020 is the year businesses will garner the benefits.