AWS whitepapers documentation change
Summary
Updated service name from 'Amazon Simple Storage Service Glacier' to 'Amazon Glacier' in introductory paragraph
Security assessment
The change appears to be a branding/naming convention update rather than addressing security concerns. No security controls, vulnerabilities, or security features are mentioned in the modified text. The rest of the security-related content about data lake best practices remains unchanged.
Diff
diff --git a/whitepapers/latest/building-data-lakes/building-data-lake-aws.md b/whitepapers/latest/building-data-lakes/building-data-lake-aws.md index 7f89e544b..b38027d66 100644 --- a//whitepapers/latest/building-data-lakes/building-data-lake-aws.md +++ b//whitepapers/latest/building-data-lakes/building-data-lake-aws.md @@ -13 +13 @@ Publication date: **November 16, 2021** ([Document history](./document-details.h -Amazon Simple Storage Service (Amazon S3) and Amazon Simple Storage Service Glacier (Amazon Glacier) provide ideal storage solutions for data lakes. Data lakes, powered by Amazon S3, provide you with unmatched availability, agility, and flexibility required to combine different types of data and analytics approaches to gain deeper insights, in ways that traditional data silos and data warehouses cannot. In addition, data lakes built on Amazon S3 integrate with other analytical services for ingestion, inventory, transformation, and security of your data in the data lake. This guide explains each of these options and provides best practices for building, securing, managing, and scaling a data lake built on Amazon S3. +Amazon Simple Storage Service (Amazon S3) and Amazon Glacier (Amazon Glacier) provide ideal storage solutions for data lakes. Data lakes, powered by Amazon S3, provide you with unmatched availability, agility, and flexibility required to combine different types of data and analytics approaches to gain deeper insights, in ways that traditional data silos and data warehouses cannot. In addition, data lakes built on Amazon S3 integrate with other analytical services for ingestion, inventory, transformation, and security of your data in the data lake. This guide explains each of these options and provides best practices for building, securing, managing, and scaling a data lake built on Amazon S3.