Natural Intelligence (NI), a leading player in multi-category marketplaces, outlines its experience in migrating to Apache Iceberg in this insightful blog post. NI emphasizes its innovative methods and the valuable lessons learned throughout the process—offering guidance for other companies contemplating a similar transition. Instead of delving into the technical details of Apache Iceberg, this article focuses on the practical challenges and solutions faced during the migration, a hurdle that many organizations are currently navigating.
Amazon SageMaker Lakehouse has introduced support for attribute-based access control (ABAC) in conjunction with AWS Lake Formation. This enhancement, utilizing AWS Identity and Access Management (IAM) principals and session tags, simplifies data access management, creation of grants, and ongoing maintenance. In this post, we will guide you through the initial steps to get started with SageMaker Lakehouse and ABAC.
We’re also excited to announce a new visual interface for OpenSearch Ingestion, allowing users to efficiently create and manage data pipelines directly from the AWS Management Console. This feature enables the rapid construction of pipelines in just minutes, eliminating the need for complex manual configurations. We will explore how these features can help speed up your data ingestion projects.
In addition, this article demonstrates how to read and write to Apache Iceberg tables using AWS Lake Formation’s hybrid access mode. You’ll learn how to leverage Lake Formation for read access while continuing to utilize IAM policy-based permissions for write workloads, including schema updates and the upsert of data records.
Furthermore, Amazon SageMaker Lakehouse now integrates seamlessly with Amazon S3 Tables, marking it as the first cloud object store to support Apache Iceberg natively. This integration empowers users to utilize various analytics services effectively.
For those looking to build unified pipelines across multiple AWS accounts and regions, we illustrate how Amazon Managed Workflows for Apache Airflow (MWAA) can facilitate centralized orchestration while distributing data processing and machine learning tasks for enhanced performance and compliance.
Additionally, we walk you through the integration of ThoughtSpot with Amazon Redshift via AWS IAM Identity Center, providing a secure and efficient analytics environment that allows teams to focus on gaining valuable business insights.
Lastly, the latest enhancement in the search functionality of Amazon SageMaker Unified Studio allows for precise technical identifier searches, streamlining data discovery.
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