AWS Big Data Blog
Category: Application Integration
How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes
ANZ Institutional Division has transformed its data management approach by implementing a federated data platform based on data mesh principles. This shift aims to unlock untapped data potential, improve operational efficiency, and increase agility. The new strategy empowers domain teams to create and manage their own data products, treating data as a valuable asset rather than a byproduct. This post explores how the shift to a data product mindset is being implemented, the challenges faced, and the early wins that are shaping the future of data management in the Institutional Division.
Introducing Amazon MWAA micro environments for Apache Airflow
Today, we’re excited to announce mw1.micro, the latest addition to Amazon MWAA environment classes. This offering is designed to provide an even more cost-effective solution for running Airflow environments in the cloud. With mw1.micro, we’re bringing the power of Amazon MWAA to teams who require a lightweight environment without compromising on essential features. In this post, we’ll explore mw1.micro characteristics, key benefits, ideal use cases, and how you can set up an Amazon MWAA environment based on this new environment class.
Introducing simplified interaction with the Airflow REST API in Amazon MWAA
Today, we are excited to announce an enhancement to the Amazon MWAA integration with the Airflow REST API. This improvement streamlines the ability to access and manage your Airflow environments and their integration with external systems, and allows you to interact with your workflows programmatically. The Airflow REST API facilitates a wide range of use cases, from centralizing and automating administrative tasks to building event-driven, data-aware data pipelines. In this post, we discuss the enhancement and present several use cases that the enhancement unlocks for your Amazon MWAA environment.
Access private code repositories for installing Python dependencies on Amazon MWAA
This post demonstrates a method to selectively install Python dependencies based on the Amazon MWAA component type (web server scheduler, or worker) from a Git repository only accessible from your virtual private cloud (VPC).
Enrich your serverless data lake with Amazon Bedrock
Organizations are collecting and storing vast amounts of structured and unstructured data like reports, whitepapers, and research documents. By consolidating this information, analysts can discover and integrate data from across the organization, creating valuable data products based on a unified dataset. This post shows how to integrate Amazon Bedrock with the AWS Serverless Data Analytics Pipeline architecture using Amazon EventBridge, AWS Step Functions, and AWS Lambda to automate a wide range of data enrichment tasks in a cost-effective and scalable manner.
How ZS built a clinical knowledge repository for semantic search using Amazon OpenSearch Service and Amazon Neptune
In this blog post, we will highlight how ZS Associates used multiple AWS services to build a highly scalable, highly performant, clinical document search platform. This platform is an advanced information retrieval system engineered to assist healthcare professionals and researchers in navigating vast repositories of medical documents, medical literature, research articles, clinical guidelines, protocol documents, […]
How Kaplan, Inc. implemented modern data pipelines using Amazon MWAA and Amazon AppFlow with Amazon Redshift as a data warehouse
Kaplan, Inc. provides individuals, educational institutions, and businesses with a broad array of services, supporting our students and partners to meet their diverse and evolving needs throughout their educational and professional journeys. In this post, we discuss how the Kaplan data engineering team implemented data integration from the Salesforce application to Amazon Redshift. The solution uses Amazon Simple Storage Service as a data lake, Amazon Redshift as a data warehouse, Amazon Managed Workflows for Apache Airflow (Amazon MWAA) as an orchestrator, and Tableau as the presentation layer.
Optimize cost and performance for Amazon MWAA
Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed service for Apache Airflow that allows you to orchestrate data pipelines and workflows at scale. With Amazon MWAA, you can design Directed Acyclic Graphs (DAGs) that describe your workflows without managing the operational burden of scaling the infrastructure. In this post, we provide guidance […]
How Amazon GTTS runs large-scale ETL jobs on AWS using Amazon MWAA
The Amazon Global Transportation Technology Services (GTTS) team owns a set of products called INSITE (Insights Into Transportation Everywhere). These products are user-facing applications that solve specific business problems across different transportation domains: network topology management, capacity management, and network monitoring. As of this writing, GTTS serves around 10,000 customers globally on a monthly basis, […]
Integrate Amazon MWAA with Microsoft Entra ID using SAML authentication
Amazon Managed Workflows for Apache Airflow (Amazon MWAA) provides a fully managed solution for orchestrating and automating complex workflows in the cloud. Amazon MWAA offers two network access modes for accessing the Apache Airflow web UI in your environments: public and private. Customers often deploy Amazon MWAA in private mode and want to use existing […]