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Author visual ETL flows on Amazon SageMaker Unified Studio (preview)

AWS Big Data

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.

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Introducing generative AI upgrades for Apache Spark in AWS Glue (preview)

AWS Big Data

Organizations run millions of Apache Spark applications each month on AWS, moving, processing, and preparing data for analytics and machine learning. Data practitioners need to upgrade to the latest Spark releases to benefit from performance improvements, new features, bug fixes, and security enhancements. Original code (Glue 2.0)

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Streamline AI-driven analytics with governance: Integrating Tableau with Amazon DataZone

AWS Big Data

Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and from third-party sources. Using Amazon DataZone lets us avoid building and maintaining an in-house platform, allowing our developers to focus on tailored solutions.

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Recap of Amazon Redshift key product announcements in 2024

AWS Big Data

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

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Expand data access through Apache Iceberg using Delta Lake UniForm on AWS

AWS Big Data

The landscape of big data management has been transformed by the rising popularity of open table formats such as Apache Iceberg, Apache Hudi, and Linux Foundation Delta Lake. These formats, designed to address the limitations of traditional data storage systems, have become essential in modern data architectures.

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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

The need to integrate diverse data sources has grown exponentially, but there are several common challenges when integrating and analyzing data from multiple sources, services, and applications. First, you need to create and maintain independent connections to the same data source for different services.

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Demystify data sharing and collaboration patterns on AWS: Choosing the right tool for the job

AWS Big Data

Data is the most significant asset of any organization. However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture.