With Snowpark and Java/Scala UDFs, Protegrity Empowers Organizations to Easily Deploy Data Anonymization for Secure AI and Data-Sharing Initiatives
Protegrity, a global leader in data security, today announced support for Snowpark, a new developer experience from Snowflake, the Data Cloud company, as well as support for Java and Scala user-defined functions (UDFs). With support for Snowpark and UDFs, Protegrity is expanding its data-privacy capabilities available within the Snowflake platform to deliver powerful data-anonymization technology to mutual customers. Snowflake and Protegrity enable data engineers, data scientists, and developers to take advantage of Snowflake’s powerful platform capabilities while reducing data-privacy risk for AI and machine-learning training and analysis, as well as data sharing with third parties.
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“Our partnership with Snowflake enables organizations to rapidly accelerate the use of data to transform their business, while ensuring sensitive data is protected every step of the way,” said Rick Farnell, President and CEO of Protegrity. “With support for Snowpark, customers can easily tap into Protegrity’s highly secure data-anonymization technology. This provides faster access to critical analytics data and dramatically shortens the time to business insights, equipping our mutual customers with the tools they need to safely pursue secure AI, machine learning, and data sharing.”
The latest support for Snowpark and UDFs builds on Protegrity’s existing partnership and integration with the Snowflake ecosystem. The Protegrity for Snowflake solution combines Snowflake’s Data Cloud capabilities with the ability to extend internal data-security policies to Snowflake to keep sensitive data private. Snowflake provides built-in data security and governance with its unique architecture, while Protegrity protects the privacy of the individuals associated with that data before it even reaches Snowflake. This allows businesses to safely unlock the value of sensitive data without compromising privacy.
“We are encouraged by Protegrity’s strong support for Snowpark, which can be transformative for many businesses as they pursue innovation with analytics and AI initiatives,” said Tarik Dwiek, Sr. Director Technology Alliances at Snowflake. “As Snowflake continues to make strides to mobilize the world’s data, partners like Protegrity give our customers greater flexibility around how they protect data residing within the Snowflake ecosystem.”
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Prior to Snowpark, the majority of users interacted with Snowflake through SQL. With Java and Scala UDFs – now available in public preview – data teams and software developers can work in their preferred development environment and programming languages. This improves the overall operational efficiency of teams by simplifying the preparation and protection of data for AI and protected data sharing.
Protegrity Delivers Powerful Anonymization for Snowpark Users
Anonymization is a strong method of data protection that adheres to stringent data regulations and high customer expectations for privacy. Through user-specified privacy models, Protegrity anonymizes sensitive elements of any data set. By completely anonymizing sensitive fields, Protegrity renders any protected data out of scope for privacy frameworks such as HIPAA, GDPR, and many others.
Protegrity’s anonymization library through Snowpark simplifies the protection of data for AI and secure data sharing. Anonymization algorithms require numerous iterations to find the privacy-protected dataset with the highest utilization. By leveraging Snowflake’s near-infinite scalability, Protegrity efficiently runs anonymization algorithms within Snowflake – without needing to remove data from the platform for processing – providing better performance and a seamless user experience.
Farnell continued, “Whether tokenizing data or applying privacy models, Protegrity gives businesses full control over how their data is protected, with the confidence of knowing that data will remain secure wherever it may reside. As a result, businesses can safely leverage their data to pursue innovation through AI without worrying about putting customers, employees, or intellectual property at risk.”
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