Making Cloud Big Data Platforms Open and Secure with Dynamic Data Authorization

Cloud big data platforms like Amazon EMR are popular because they offer tremendous flexibility to use open source frameworks like Apache Spark, Apache Hive and Presto, and they efficiently provision compute resources as needed. Because organizations do not have to invest time and money in their own infrastructure, they can greatly reduce computing costs and accelerate time-to-answer. There’s a catch, however. With openness and flexibility come a responsibility to use confidential, personally identifiable and regulated data responsibly. Simply evaluating how to enforce data authorization policies across a variety of user activities on open platforms can be time-consuming, and for that reason some organizations do not even consider cloud compute for big data when working with sensitive data. Now you can.

Ready to Get Started? Here Are Some Resources to Help

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Simplifying Data Mesh for Self-Service Analytics on an Open Data Lakehouse

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Dremio Upgrade Testing Framework

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Operating Dremio Cloud Runbook

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