Category: Amazon DataZone

In this post, we show you how Covestro transformed its data architecture by implementing Amazon DataZone and AWS Serverless Data Lake Framework, transitioning from a centralized data lake to a data mesh architecture. The implementation enabled streamlined data access, better data quality, and stronger governance at scale, achieving a 70% reduction in time-to-market for over 1,000 data pipelines.

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.

In this post, we introduce Amazon DataZone and explore how Volkswagen used Amazon DataZone to build their data mesh, tackle the challenges encountered, and break the data silos.

Don’t miss our upcoming webinar! Register here to join AWS experts as they dive deeper and share practical insights for upgrading to SageMaker. Amazon DataZone and Amazon SageMaker announced a new feature that allows an Amazon DataZone domain to be upgraded to the next generation of SageMaker, making the investment customers put into developing Amazon […]

In this post, we explore its real-world impact through the lens of an ecommerce company striving to boost their bottom line. To illustrate this practical application, we walk you through how you can use the prebuilt integration between SageMaker Catalog and AWS Glue crawlers to automatically capture lineage for data assets stored in Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB.

In this post, we explore how Furuno Electric built a comprehensive data management foundation using Amazon DataZone and other AWS services to transform from a traditional manufacturing company to a data-driven business.

This post walks you through how to use the OpenLineage-compatible API of SageMaker or Amazon DataZone to push data lineage events programmatically from tools supporting the OpenLineage standard like dbt, Apache Airflow, and Apache Spark.

In this post, we will cover how you can use Amazon DataZone to facilitate data collaboration between AWS accounts.

In this post, we explore how AWS customers can extend Amazon DataZone to support streaming data such as Amazon Managed Streaming for Apache Kafka (Amazon MSK) topics. Developers and DevOps managers can use Amazon MSK, a popular streaming data service, to run Kafka applications and Kafka Connect connectors on AWS without becoming experts in operating it.

In this post, we show you how EUROGATE uses AWS services, including Amazon DataZone, to make data discoverable by data consumers across different business units so that they can innovate faster. Two use cases illustrate how this can be applied for business intelligence (BI) and data science applications, using AWS services such as Amazon Redshift and Amazon SageMaker.