Exasol announced a strategic partnership with Protegrity. Together, Exasol and Protegrity enable organizations to run analytics against sensitive and private data securely and at scale. The new joint solution leverages the native Protegrity connector and the in-memory, MPP engine from Exasol, providing customers with advanced tokenization technology to identify, protect and analyze sensitive data faster than ever before. Offering flexible deployment options, this powerful new solution ensures that sensitive data is always protected no matter where it resides – on-premise, in the cloud or in a hybrid infrastructure. As organizations satisfy regulatory requirements such as HIPAA, PCI DSS, and GDPR, they must securely tap into large amounts of data with confidence. Many are turning to the Exasol and Protegrity solution to identify, secure and analyze sensitive data in-memory and scale linearly, unlocking new insights and hastening innovations while ensuring that no sensitive data is compromised. While organizations are moving towards data-driven decision making, many have been hampered by concerns over managing data security and compliance requirements in their analytics workflow. This new joint solution dispels those fears by enabling them to run analytics against sensitive and private data securely and at scale. The joint solution also allows organizations to include sensitive data in artificial intelligence and machine learning models. AI and ML projects require training algorithms with a variety of data, including sensitive data, within the enterprise. Data science teams can now access sensitive data that is anonymized in Exasol, so they can test out more scenarios than they could previously to improve model accuracy and reduce AI bias. To accelerate AI in production, the data science team can run models directly on Exasol’s in-memory engine, without exporting the data to a different system.