20 Apr Case Study: Protegrity Tokenization For Google Cloud
See original case study on Akvelon’s Google Cloud Partner Advantage Profile .
Protegrity is a global leader in data security, protecting sensitive data everywhere and future-proofing businesses as data-privacy regulations evolve. The Protegrity Data Protection Platform secures the privacy of more than two billion individuals, offering personalized data-centric security strategies to meet customers’ specific needs.
Industry: Software & Internet
Primary project location: United States
“In collaboration with Akvelon, Protegrity utilized a Dataflow Flex template that helps us enable customers to tokenize and detokenize streaming and batch data from a fully managed Google Cloud Dataflow service. We appreciate Akvelon’s support as a trusted partner with Google Cloud expertise”
– Jay Chitnis, VP of Partners and Business Development, Protegrity
Through Akvelon’s ongoing partnership with Protegrity, Akvelon designed and developed a Google Dataflow template that allows Protegrity’s customers to tokenize and detokenize streaming and batch data.
Protegrity wanted to improve its customers’ experience and platform capabilities by enabling users to tokenize and detokenize streaming and batch data from the fully managed Google Cloud Dataflow service. Protegrity realized that its best option to achieve this was to select a trusted partner with extensive expertise in data and analytics to design and develop the solution.
Akvelon designed and implemented a Dataflow Flex template that customers can deploy to tokenize and detokenize sensitive data using the Protegrity Data Protection Platform. The template supports streaming and batch data sources, multiple data formats. While the template supports open-source Apache Beam, the Dataflow runner brings additional optimizations provided for stateful processing.
Akvelon’s solution enabled Protegrity to provide customers the ability to tokenize sensitive data using the Protegrity Data Protection Platform and Google Cloud Dataflow, optimize performance using stateful processing, and make Apache Beam and Google Cloud Dataflow open-source templates available to all of the open-source community.