Musings on data, privacy, and a few product announcements

U.S. Air Force Explores Data Synthesis with Tonic

Marking a significant milestone in our startup’s timeline, we’re excited to announce that Tonic has won a Small Business Innovation Research (SBIR) contract from the U.S. Air Force to respond to its data synthesis and generation needs. Under the aegis of this award, we’re investigating how our platform can be adapted to generate synthetic images, along with the structured data found in the images’ reports, for a number of units within the AF.

Data Security Risks Greater Than Ever With Dev Teams Working From Home

Just when we thought data proliferation couldn’t get any worse, welcome to an entire world of developers working from home. Using production data in staging is problematic in and of itself. Using production data in staging on home computers scattered to the four winds? To put it lightly: yikes! How is your team handling this new data security/data access challenge? Have you found a workaround that keeps your developers productive and your customers’ data safe?

Partnering with Spirion in an Industry First to Bolster Data Discovery with Data Anonymization

Hot on the heels of the official press release, we’re very excited to announce our partnership with data security pioneer Spirion. Spirion’s award-winning data privacy tools include data discovery, persistent classification, and behavior software and services that enable companies to reduce their sensitive data footprint and minimize the risk of cyberattacks and regulatory violations. Our integration is designed to answer the need for Spirion’s users to retain the utility of their data, thanks to realistic data synthesis, while complying with consumer rights to be forgotten and the data processing and de-identification requirements of GDPR and CCPA.

Your Data is Safe — Math Guarantees It!

Hot off the heels of the Privacy Hub, we’re introducing more privacy protecting features to Tonic! Today we’re excited to announce the introduction of differential privacy to Tonic. Differential privacy gives you confidence and visibility into the safety of the data Tonic produces. For the uninitiated, differential privacy is a mathematical guarantee about the privacy of a process. In this first release only certain data types will support differential privacy, but expect more in coming releases.

Introducing Privacy Hub, DLP for Data Governance

There’s an old adage that goes something like “if you can’t measure it, you can’t fix it.” Well we’re giving you the tools to measure and fix at the same time. Our new privacy hub feature, not only finds your sensitive data, but also secures it once detected. Announcing Privacy Hub Driven by dozens of customer requests to solve data governance and proliferation challenges, we’re launching a capabilities to explicitly track and transform data as part of an automated process.

Getting the Data You Want Out of JSON with JSONPath

In the last decade, JSON has become the dominant data-interchange format and the backbone of most NoSQL databases. [1] So it’s not surprising that the ISO SQL standard added JSON support to their specification in late 2016 [2], and most popular SQL databases, like Postgres, one of our favorites, have upped their JSON game over the past few years. I could take a moment now to weigh in on the NoSQL vs SQL debate, and these developments definitely make that choice more complex, but I’ll save that for another time.

The Consumer Right that Makes NYPA the Toughest Privacy Act for AI

The New York Privacy Act (NYPA) made quite a splash when introduced in the NY State Senate this past May. Like the summer’s first cannon ball into the deep end, it sent waves through the data privacy world, with harbinger-of-doom headlines proclaiming it a “sweeping,” “even bolder”, “considerably tougher”, “stringent”, nay, the “strictest” data privacy bill to date. And the headlines weren’t wrong. The bill stands to impact companies of any size (including non-profits) doing business in or even so much as producing “products or services that are intentionally targeted to residents” of New York.

Database Subsetting Is Not a Piece of Cake, So We Baked Condenser 2.0 Just for You

It’s hard to believe it but it’s been a year since we released the original version of Condenser, our open source database subsetting tool. Since then, Condenser has been deployed in a variety of situations, and we’ve learned a bunch along the way, specifically, what you need to make it work best for you. The culmination of this is the release of Condenser 2.0! Rejoice 🎉! In this post, we’ll explore what we’ve learned about subsetting and the challenges our new release helps you overcome.

Simple Foreign Key Detection

For better or worse, sometimes we omit foreign key constraints on columns with a foreign key relationship. Sometimes we do this for performance reasons, sometimes it’s the behavior of a framework we’re using, and sometimes it’s desirable semantically. Whatever the case, often times its handy to list the foreign keys in the database that aren’t constraints; and that’s where this simple tool we built comes in handy. Finding Foreign Keys Without further ado, here’s a tool for finding implicit foreign keys in a Postgres or MySQL database.

Masquerade: A Postgres Proxy to Mask Data in Realtime

Caption: Left side shows psql connected to the proxy while the right side shows psql connected directly to the DB. Redact and Replace in Realtime with no Additional Infrastructure Many of our customers have multiple databases, complex application logic, and limited time. One of the easiest ways to protect your data is to add a proxy between the consumer (analyst, application, developer, etc) and the data base. Since the proxy doesn’t clone the data, there are no additional infrastructure costs.
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