Free Guide

Compliant and Secure Cloud Data Lakes: 3 Practical Solutions

The growth of cloud data lakes presents new challenges when it comes to protecting personal data. . When data is stored in unstructured object stores such as Amazon S3, Google Cloud Storage, and Azure Blob Store, it can be difficult to pinpoint the location of sensitive data in order to create an effective permissions policy. Regulatory requirements such as the GDPR and CCPA add an extra layer of complexity.

Dealing with security, compliance, and privacy challenges in the data lake age requires a new set of tools and approaches. In this digital guide, we present three of these challenges and show practical solutions you can implement using Upsolver.

In this guide:

– Removing data to comply with GDPR or CCPA requests

– Tokenizing PII on Amazon S3 storage

– Separating data from different customers in user-facing analytics architectures

– Best practices, examples, and diagrams

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This guide is for:

  • Data engineering leaders who want to understand how to solve practical security and privacy challenges on cloud data lakes
  • CIOs who want to ensure their organization is compliant and reduce operational risks
  • CTOs who want to discover cloud architecture best practices

Powering data lakes for data-intensive companies