Protegrity Partners With Google Cloud to Support BigQuery Remote Functions
Protegrity, a global leader in data security, today announced it has partnered with Google Cloud to support the upcoming release of BigQuery remote functions. First announced at Google Cloud Next ‘21 in October, BigQuery remote functions offer Google Cloud customers the ability to extend BigQuery with their own external code. With support for remote functions, Protegrity adds an additional layer of data protection, while enabling customers to deliver faster, more robust analysis through Google Cloud BigQuery.
Protegrity’s partnership with Google Cloud lays a strong foundation to deliver de-identified data sets across many Google Cloud services. In addition to its support for Google Cloud remote functions, Protegrity also announced the availability of the Cloud API for Google Cloud, a serverless API that can be used to integrate data protection into cloud services and ETL workflows, as well as the Snowflake Protector on Google Cloud.
“Through our partnership with Google Cloud, one of the foremost leaders in cloud computing and data analytics, we are enabling our mutual customers to accelerate data innovation without compromising privacy,” said Jeffrey Breen, executive vice president of product and strategy at Protegrity. “Joining forces with Google Cloud delivers a privacy-by-design approach to more customers, enhancing their ability to bring to life the value of their sensitive data, pursue secure data collaboration, and innovate through advanced analytics.“
Protegrity’s Support for BigQuery Enables Secure Analytics at Scale
BigQuery’s serverless architecture offers businesses the ability to operate at scale and speed, which allows for faster analytics over large data sets. With Protegrity’s remote functions support, customers can now securely leverage data sets that contain personally identifiable information. In combination with BigQuery’s out-of-the-box security features, Protegrity’s fine-grained data protection gives customers a high level of confidence to achieve compliance with strict data privacy regulations and internal security and risk management policies. This allows businesses to deliver faster, more robust data analysis through BigQuery, without jeopardizing privacy.
Protegrity’s vaultless tokenization uses a data de-identification methodology to protect the privacy of individuals by tokenizing personal identifiers and quasi-identifiers. Tokenizing data before it moves to the cloud delivers a “Security by Design” framework and underpins a customer’s ability to rapidly innovate new applications and analytical models while preserving privacy. Protegrity’s persistent data protection element ensures that data is protected in the case of intrusion, configuration error, or other cases of data exposure.
“As data and analytics have become increasingly important to business growth and innovation, so too has data privacy and security,” said Sudhir Hasbe, Director, Product Management, Google Cloud. “We’re excited for BigQuery remote functions to be generally available for customers and to provide even more ways to run data analysis with speed, privacy, and security in partnership with Protegrity.”
Protegrity’s support for BigQuery remote functions will be generally available in Q1 2022.
Protegrity Cloud API and Snowflake Protector Safeguard Sensitive Data
Protegrity also announced two new data protectors for Google Cloud customers, including the Cloud API, a serverless API that can be used to integrate data protection into cloud services and ETL workflows, as well as the Snowflake Protector on Google Cloud.
- Cloud API: The Cloud API is a serverless API that allows developers to integrate data protection into custom applications and ETL workflows in the cloud. These components operate on each platform’s native Function-As-A-Service (FaaS) for full cloud, elastic scaling.
- Snowflake Protector : The Snowflake Protector is a purpose-built protector that integrates seamlessly with Snowflake SQL to protect or unprotect data. It has been benchmarked to blazing speeds with elastic scaling to support the largest workloads.
“In today’s data economy, a company’s competitive advantage lies in their ability to harness the power of the cloud for advanced analytics,” said Matt Hutton, vice president of cloud engineering at Protegrity. “With Protegrity’s advanced data protection capabilities now available for Google Cloud, organizations can generate valuable insights faster and more securely than ever before.”
To learn more about Protegrity’s support for Google Cloud, please visit the blog.
Protegrity, a global leader in data security, protects sensitive data everywhere and future-proofs businesses as data-privacy regulations evolve. Maintaining privacy today across distributed data has become impossibly complicated. With Protegrity, enterprises can secure data wherever it resides, control how it’s protected, and have confidence that data is safe, even if a breach occurs. The Protegrity Data Protection Platform is a modern alternative to traditionally complex data-protection methods that leave gaps in security. Whether encrypting, tokenizing, or applying privacy models, Protegrity protects data at the speed of business. Deep integrations with Snowflake, Amazon Redshift, Teradata, Oracle, Microsoft SQL Server, Cloudera, Databricks, and many other enterprise applications ensure that data remains fully protected in hybrid-cloud, multi-cloud, and on-premises environments. The platform’s fine-grained data protection anonymizes personally identifiable information (PII) that’s used in AI and machine learning models, providing faster access to critical analytics data and dramatically shortening the time to business insights. Protegrity protects the sensitive data of more than two billion individuals across global enterprises, including four of the world’s 15 largest banks, four out of 10 of the top health insurance providers, and three of the world’s leading multinational companies. With more than two decades of industry-leading innovation, Protegrity allows businesses to finally tap into the value of their data and accelerate digital transformation timelines – without jeopardizing individuals’ fundamental right to privacy.
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