AWS FeedAutomate the archival and deletion of sensitive data using Amazon Macie Customers are looking for ways to securely and cost-efficiently manage large volumes of sensitive data archival and deletion in their data lake by following regulations and data protection and privacy laws, such as GDPR, POPIA, and LGPD. This post describes a way to…
AWS FeedIn the Works – AWS Region in Tel Aviv, Israel We launched three AWS Regions (Italy, South Africa, and Japan) in the last 12 months, and are working on regions in Australia, Indonesia, Spain, India, Switzerland, and the United Arab Emirates. Tel Aviv, Israel in the WorksToday I am happy to announce that the…
AWS FeedBuild patient outcome prediction applications using Amazon HealthLake and Amazon SageMaker Healthcare data can be challenging to work with and AWS customers have been looking for solutions to solve certain business challenges with the help of data and machine learning (ML) techniques. Some of the data is structured, such as birthday, gender, and marital…
AWS FeedOptimizing the Cost of Your SaaS Environment with the AWS Well-Architected SaaS Lens By Kevin Mueller, Sr. Partner Solutions Architect – AWS SaaS FactoryBy Oren Reuveni, Principal Partner Solutions Architect – AWS SaaS Factory Capturing, managing, and analyzing costs is an essential part of any software-as-a-service (SaaS) business. In a multi-tenant environment, where tenant…
AWS FeedDOCOMO empowers business units with self-service knowledge access thanks to agile AWS QuickSight business intelligence NTT DOCOMO is the largest telecom company in Japan. It provides innovative, convenient, and secure mobile services that enable customers to realize smarter lives. More than 73 million customers in Japan connect through its advanced wireless networks, including a…
AWS FeedAmazon SageMaker Pipelines now supports callback capability Amazon SageMaker Pipelines, the first purpose-built continuous integration and continuous delivery (CI/CD) service for machine learning (ML), now supports a new callback step that allows customers to integrate any task or job outside Amazon SageMaker as a step in the model building pipeline. When a callback step…