Customers often want to augment and enrich SAP source data with other non-SAP source data. Such analytic use cases can be enabled by building a data warehouse or data lake. Customers can now use the AWS Glue SAP OData connector to extract data from SAP. The SAP OData connector supports both on-premises and cloud-hosted (native … Read more
Most companies have adopted a diverse set of software as a service (SaaS) platforms to support various applications. The rapid adoption has enabled them to quickly streamline operations, enhance collaboration, and gain more accessible, scalable solutions for managing their critical data and workflows. More companies have realized there is an opportunity to integrate, enhance, and … Read more
The AWS Glue Data Catalog now automates generating statistics for new tables. These statistics are integrated with the cost-based optimizer (CBO) from Amazon Redshift Spectrum and Amazon Athena, resulting in improved query performance and potential cost savings. Queries on large datasets often read extensive amounts of data and perform complex join operations across multiple datasets. … Read more
Organizations are building data-driven applications to guide business decisions, improve agility, and drive innovation. Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data. Data scientists … Read more
In today’s rapidly evolving financial landscape, data is the bedrock of innovation, enhancing customer and employee experiences and securing a competitive edge. Recognizing this paradigm shift, ANZ Institutional Division has embarked on a transformative journey to redefine its approach to data management, utilization, and extracting significant business value from data insights. Like many large financial … Read more
This week on the keynote stages at AWS re:Invent 2024, you heard from Matt Garman, CEO, AWS, and Swami Sivasubramanian, VP of AI and Data, AWS, speak about the next generation of Amazon SageMaker, the center for all of your data, analytics, and AI. The relationship between analytics and AI is rapidly evolving. Our customers … Read more
Yesterday, we announced Amazon SageMaker Unified Studio (Preview), an integrated experience for all your data and AI and Amazon SageMaker Lakehouse to unify data – from Amazon Simple Storage Service (S3) to third-party sources such as Snowflake. We’re excited by how SageMaker Lakehouse helps break down data silos, but we also know customers don’t want … Read more
With the growing emphasis on data, organizations are constantly seeking more efficient and agile ways to integrate their data, especially from a wide variety of applications. While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, … Read more
Amazon SageMaker Unified Studio (preview) provides an integrated data and AI development environment within Amazon SageMaker. From the Unified Studio, you can collaborate and build faster using familiar AWS tools for model development, generative AI, data processing, and SQL analytics. This experience includes visual ETL, a new visual interface that makes it simple for data … Read more
In today’s data-driven world, organizations are constantly seeking efficient ways to process and analyze vast amounts of information across data lakes and warehouses. Enter Amazon SageMaker Lakehouse, which you can use to unify all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses, helping you build powerful analytics … Read more