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Recently  Srinivas Avarsala, VP, Product Management at Securiti and Norm Fjeldheim, former CIO at Illumina and Qualcomm discussed the challenges of multicloud data security and privacy in hyperscale environment.

Today, multicloud strategy is widely deployed. Research suggests that more than 80% of organizations utilize multiple Cloud Service Providers (CSPs) for various business functions. And it is a key driver for sensitive & personal data to spread across various cloud environments increasing security and privacy risks. In case of multi cloud, security and privacy risks are affected by the following factors:

  1. Challenge 1: No centralized asset inventory
    Separate console for CSPs, SaaS and non-native cloud assets contribute to a distributed asset inventory leading to blindspots in coverage.
  2. Challenge 2: Inconsistent Data Discovery Capabilities
    With fragmented data assets, organizations are forced to use various data discovery tools to detect sensitive data in them. Traditional data discovery tools offer limited coverage for sensitive data types and use unique detection technologies which can lead to inconsistent and poor discovery results.
  3. Challenge 3: Unable to detect sensitive data in large data volumes
    Traditional data discovery solutions cannot support petabytes of data stored in various data assets. Typical use-case include  - cloud data lakes, data warehouses, analytics etc.
  4. Challenge 4: Manual privacy compliance processes
    Manual techniques such as surveys and questionnaires for privacy compliance are tedious, inaccurate and can cause higher privacy risks for organizations.
  5. Challenge 5: Complex security and compliance posture
    Existing security posture management tools do not provide a sensitive data or data risk perspective for multicloud assets. This may cause false alerts and reduce productivity. To learn about these challenges & solutions, download our on-demand webinar to learn more about these challenges and solutions in much more detail.

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