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Building a GDPR compliance solution with Amazon DynamoDB

  • AWS Service Sector Industry Solutions has developed a feature that enables customers to efficiently locate and delete personal data upon request, helping them meet GDPR compliance requirements
  • The GDPR mandates organizations to obtain explicit consent before collecting personal data and provides individuals with the right to erasure.
  • The company needed a scalable, cost-effective solution to handle GDPR erasure requests.
  • The application manages extensive profile data across various services, and the process involved overcoming significant challenges related to data storage, retrieval, and deletion while also minimizing disruption to customers’ operations.
  • One of the primary design challenges was efficiently locating and purging profile data stored in Amazon S3, especially considering the terabytes of data involved.
  • For GDPR erasure of profile data in Amazon S3, the team built a custom solution predominantly using the Go programming language and aLambda function using AWS SDK for Pandas in Python.
  • The use of Parquet, a columnar storage format, allows Athena to query only the necessary columns rather than entire rows, as required with CSV files.
  • To achieve distributed mutex using DynamoDB, they used a custom mutex client.
  • The mutex client uses DynamoDB ConditionExpression to make sure the RVN has not changed from what was previously stored.
  • This solution can be adapted for other use cases requiring secure, distributed locking mechanisms or efficient data management across large datasets.

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