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Immuta Spring ‘19 Release: Automating Compliant Data Collaboration

Data analytics rarely occurs in a vacuum – analysts work together sharing scripts, dashboards, and models as they attempt to extract value from their organization’s most critical business asset: data. A common misstep is that most controls are limited to protecting the raw data, and fail to consider the data security and privacy implications that...

How Policy Leaders Can Democratize Data Ethics

Now, even Facebook’s Mark Zuckerberg is calling for GDPR-like national data regulations. His goals are laudable. He wants to give consumers more rights to control and protect their information. Yet his comments do not fully consider an often-invisible group in the world of data regulations. These are small- and medium-sized enterprises (SMEs), such as startups. Without armies...

7 Legal Principles to Stay Ahead of the Regulatory Curve

Just this year, countries that constitute 50% of the world’s GDP are considering or enforcing stricter data regulations. California, China, and Brazil, for instance, are forcing companies to safeguard and give their customers more control over their data. From fines of 2-4% of a company’s global revenue to criminal sanctions in China — to ignore...

Why Differential Privacy Should Be Top of Mind for Data Science and Governance Teams

On 30 January I taught a masterclass on de-identification organised by the Future of Privacy Forum together with Khaled El Emam from Privacy Analytics. The audience comprised industry representatives, policy and law-makers mainly from the European Union. My goal was to cover the topic of differential privacy in an easy-to-digest manner, and to highlight the...

Differential Privacy: A Sound Way to Protect Private Data

Striking the privacy-utility balance is the central challenge to organizations handling sensitive data.  Assessing the privacy side of the balance requires understanding how different privacy policies are undermined.  This post will focus on one particular attack against privacy and show how two different privacy policies respond to this attack.   In our context, a privacy-preserving...

An Ongoing Challenge for AI/ML in the Traditional Enterprise: Getting Data to the Cloud

Artificial Intelligence (AI) and Machine Learning (ML) are among the “buzziest” of the buzz words in the technology sector, especially in the cloud market.  The hyperscalers and the ISVs that surround them (Immuta included) leverage these terms heavily in their marketing material and campaigns. For the hyperscalers in particular, what are often considered “advanced services”...

Data Governance Anti-Patterns: Start From Scratch; Rinse, Repeat

This is part IV of our “Data Governance Anti-Patterns Series.” You can find part III here. Anti-patterns are behaviors that take bad problems and lead to even worse solutions. In the world of data governance, they’re everywhere. This blog’s anti-pattern again serves as an example of how initial intuition does not lend itself to a...

The Art of Making the Possible Practical: Introducing Immuta Research

Drs. Joseph Regensburger,  Alfred Rossi, and Stephen Bailey trickle in on a Monday morning. In between sips of coffee, the conversation flows from familiar domains of life — traffic, kids, the events of the weekend — to heady technical topics. Frenetic whiteboard scribbling punctuates the discussion which, today, includes how to achieve a mathematical guarantee...

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