AWS Big Data Blog

Guide to adopting Amazon SageMaker Unified Studio from ATPCO’s Journey

ATPCO is the backbone of modern airline retailing, helping airlines and third-party channels deliver the right offers to customers at the right time. ATPCO addressed data governance challenges using Amazon DataZone. SageMaker Unified Studio, built on the same architecture as Amazon DataZone, offers additional capabilities, so users can complete various tasks such as building data pipelines using AWS Glue and Amazon EMR, or conducting analyses using Amazon Athena and Amazon Redshift query editor across diverse datasets, all within a single, unified environment. In this post, we walk you through the challenges ATPCO addresses for their business using SageMaker Unified Studio.

Achieve low-latency data processing with Amazon EMR on AWS Local Zones

By deploying Amazon EMR on AWS Local Zones, organizations can achieve single-digit millisecond latency data processing for applications while maintaining data residency compliance. This post demonstrates how to use AWS Local Zones to deploy EMR clusters closer to your users, enabling millisecond-level response times.

Cluster manager communication simplified with Remote Publication

Amazon OpenSearch Service has taken a significant leap forward in scalability and performance with the introduction of support for 1,000-node OpenSearch Service domains capable of handling 500,000 shards with OpenSearch Service version 2.17. This post explains cluster state publication, Remote Publication, and their benefits in improving durability, scalability, and availability.

Enhance Amazon EMR observability with automated incident mitigation using Amazon Bedrock and Amazon Managed Grafana

In this post, we demonstrate how to integrate real-time monitoring with AI-powered remediation suggestions, combining Amazon Managed Grafana for visualization, Amazon Bedrock for intelligent response recommendations, and AWS Systems Manager for automated remediation actions on Amazon Web Services (AWS).

Build data pipelines with dbt in Amazon Redshift using Amazon MWAA and Cosmos

In this post, we explore a streamlined, configuration-driven approach to orchestrate dbt Core jobs using Amazon Managed Workflows for Apache Airflow (Amazon MWAA) and Cosmos, an open source package. These jobs run transformations on Amazon Redshift. With this setup, teams can collaborate effectively while maintaining data quality, operational efficiency, and observability.

The Amazon SageMaker lakehouse architecture now automates optimization configuration of Apache Iceberg tables on Amazon S3

The Amazon SageMaker lakehouse architecture now automates optimization of Iceberg tables stored in Amazon S3 with catalog-level configuration, optimizing storage in your Iceberg tables and improving query performance. This post demonstrates an end-to-end flow to enable catalog level table optimization setting.

Create an OpenSearch dashboard with Amazon OpenSearch Service

This post demonstrates how to harness OpenSearch Dashboards to analyze logs visually and interactively. With this solution, IT administrators, developers, and DevOps engineers can create custom dashboards to monitor system behavior, detect anomalies early, and troubleshoot issues faster through interactive charts and graphs.