Описание DataFleets - Federated Learning and SQL
“Creating machine learning models that learn across all of our customers without aggregating any data. Now that’s a killer app.” - Lead Data Scientist at a Fortune 500 Company
Introducing DataFleets. The world's first cloud platform for unified and privacy-preserving enterprise data analytics powered by Federated Learning. It's never been easier to securely bridge data silos and create new data-driven products with strong network effects. DataFleets allows data teams to ship their analytics out to data, wherever it resides, analyzing it compliantly (e.g., GDPR, CCPA) with game-changing results: 10x available data and 10x speed in accessing it.
Offering enterprise-ready, cloud-agnostic analytics with unparalleled performance
DataFleets' tech has first-class support for a full suite of data science and machine learning tools, allowing no change in workflow and unparalleled performance.
Our flexible and open-source technology makes it easy to deploy Privacy Enhancing Technologies (PETs) such as federated learning, differential privacy, secure multi-party computation, homomorphic encryption, and attack-based privacy evaluation. You'll never need lossy data masking or tokenization again.
Our integrations and partnerships span Apache Spark, Apache Arrow, Tensorflow, Keras, Scikit Learn, H20.ai, PySyft, PyTorch, Kubernetes, Amazon Web Services (AWS), Google Cloud (GCP), Alibaba Cloud, and NVIDIA. We offer first-class support for Microsoft Azure and Microsoft WhiteNoise differential privacy platform.
Measurably improve your data security, privacy, and compliance
DataFleets provides robust and auditable security and privacy guarantees approved by regulators. We uphold three best-practice principles:
No data ever moves from its original and secure location
No row-level data is ever exposed to an analyst
All analytics results are anonymized to best-in-class standards like GDPR, CCPA, and HIPAA
Ready to accelerate your data teams' agility and speed?
Learn more at www.datafleets.com
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