AWS Big Data Blog

In this post, we show you the upgrade process from DC2 instances to Amazon Redshift Serverless. By using Amazon Redshift Serverless, you can run and scale analytics without managing data warehouse infrastructure.

Stifel Financial Corp, a diversified financial services holding company is expanding its data landscape that requires an orchestration solution capable of managing increasingly complex data pipeline operations across multiple business domains. Traditional time-based scheduling systems fall short in addressing the dynamic interdependencies between data products, requires event-driven orchestration. Key challenges include coordinating cross-domain dependencies, maintaining data consistency across business units, meeting stringent SLAs, and scaling effectively as data volumes grow. Without a flexible orchestration solution, these issues can lead to delayed business operations and insights, increased operational overhead, and heightened compliance risks due to manual interventions and rigid scheduling mechanisms that cannot adapt to evolving business needs. In this post, we walk through how Stifel Financial Corp, in collaboration with AWS ProServe, has addressed these challenges by building a modular, event-driven orchestration solution using AWS native services that enables precise triggering of data pipelines based on dependency satisfaction, supporting near real-time responsiveness and cross-domain coordination.

In this post, we show you how to create custom notifications for events occurring in SageMaker Catalog using Amazon EventBridge, AWS Lambda, and Amazon SNS. You can expand this solution to automatically integrate SageMaker Catalog with in-house enterprise workflow tools like ServiceNow and Helix.

At Twilio, we manage a 20 petabyte-scale Amazon S3 data lake that serves the analytics needs of over 1,500 users, processing 2.5 million queries monthly and scanning an average of 85 PB of data. To meet our growing demands for scalability, emerging technology support, and data mesh architecture adoption, we built Odin, a multi-engine query platform that provides an abstraction layer built on top of Presto Gateway. In this post, we discuss how we designed and built Odin, combining Amazon Athena with open-source Presto to create a flexible, scalable data querying solution.

This post demonstrates how to configure SageMaker Unified Studio with SSO, set up projects and user onboarding, and access data securely using integrated analytics tools.

In this post, we introduce an alternative architecture to synchronize mainframe data to the cloud using Amazon Managed Streaming for Apache Kafka (Amazon MSK) for greater flexibility and scalability. This event-driven approach provides additional possibilities for mainframe data integration and modernization strategies.

As analytical demands grow, many customers are upgrading from DC2 to RA3 or Amazon Redshift Serverless, which offer independent compute and storage scaling, along with advanced capabilities such as data sharing, zero-ETL integration, and built-in artificial intelligence and machine learning (AI/ML) support with Amazon Redshift ML. This post provides a practical guide to plan your target architecture and migration strategy, covering upgrade options, key considerations, and best practices to facilitate a successful and seamless transition.

Amazon SageMaker offers a comprehensive hub that integrates data, analytics, and AI capabilities, providing a unified experience for users to access and work with their data. Through Amazon SageMaker Unified Studio, a single and unified environment, you can use a wide range of tools and features to support your data and AI development needs, including […]

In this post, we demonstrate how to build a serverless architecture that processes real-time ICU patient monitoring data using Lambda event source mapping for immediate alert generation and data aggregation, followed by persistent storage in Amazon S3 with an Iceberg catalog for comprehensive healthcare analytics.

Apache Airflow 3.x on Amazon MWAA introduces architectural improvements such as API-based task execution that provides enhanced security and isolation. This migration presents an opportunity to embrace next-generation workflow orchestration capabilities while providing business continuity. This post provides best practices and a streamlined approach to successfully navigate this critical migration, providing minimal disruption to your mission-critical data pipelines while maximizing the enhanced capabilities of Airflow 3.