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Multi-cloud Data Security and Privacy for Hyperscale Environment

A recent Gartner survey suggested that 81% of large organizations prefer to work with two or more cloud providers. Organizations choose a multi-cloud strategy to prevent lock-in & embrace best of breed functionalities.
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Speakers

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Michael Meriton

Michael Meriton

Co Founder and COO, EDM Council

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Norm Fjeldheim

Norm Fjeldheim

Former CIO for Illumina and Qualcomm

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Srinivas Avasarala

Srinivas Avasarala

Vice President, Product Management, Securiti


A recent Gartner survey suggested that 81% of large organizations prefer to work with two or more cloud providers. Organizations choose a multi-cloud strategy to prevent lock-in & embrace best of breed functionalities.

However in a multi-cloud environment, the security and privacy risks increase many-fold due to unique data security requirements for every regulation, a variety of security controls available from cloud providers and separate control/policy engine for every cloud provider.

In addition, these requirements are further complicated due to an organization's global operations in multiple jurisdictions each with their local laws that include unique data protection requirements. To reduce these risks, organizations need to start by detecting sensitive data across all cloud environments and use a central policy engine to orchestrate and enforce data security consistently across all cloud environments. In this webinar, we have discussed:

  • Major security and privacy data challenges and risks posed by multi cloud usage
  • Use AI & ML to discover sensitive data assets, type, location, jurisdiction, owners, and security posture associated with their data
  • Enforce and automate data security posture across all cloud
  • Instantly provide security and privacy reports such as article 30

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