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Amazon Q data integration adds DataFrame support and in-prompt context-aware job creation

AWS Big Data

Amazon Q data integration , introduced in January 2024, allows you to use natural language to author extract, transform, load (ETL) jobs and operations in AWS Glue specific data abstraction DynamicFrame. In this post, we discuss how Amazon Q data integration transforms ETL workflow development.

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Introducing Amazon Q data integration in AWS Glue

AWS Big Data

Today, we’re excited to announce general availability of Amazon Q data integration in AWS Glue. Amazon Q data integration, a new generative AI-powered capability of Amazon Q Developer , enables you to build data integration pipelines using natural language.

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Bridging the gap between mainframe data and hybrid cloud environments

CIO Business Intelligence

Additionally, integrating mainframe data with the cloud enables enterprises to feed information into data lakes and data lake houses, which is ideal for authorized data professionals to easily leverage the best and most modern tools for analytics and forecasting.

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Data transformation takes flight at Atlanta’s Hartsfield-Jackson airport

CIO Business Intelligence

The original proof of concept was to have one data repository ingesting data from 11 sources, including flat files and data stored via APIs on premises and in the cloud, Pruitt says. There are a lot of variables that determine what should go into the data lake and what will probably stay on premise,” Pruitt says.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

cycle_end"', "sagemakedatalakeenvironment_sub_db", ctas_approach=False) A similar approach is used to connect to shared data from Amazon Redshift, which is also shared using Amazon DataZone. While real-time data is processed by other applications, this setup maintains high-performance analytics without the expense of continuous processing.

IoT 111
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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Author data integration jobs with an interactive data preparation experience with AWS Glue visual ETL

AWS Big Data

Now you can author data preparation transformations and edit them with the AWS Glue Studio visual editor. The AWS Glue Studio visual editor is a graphical interface that enables you to create, run, and monitor data integration jobs in AWS Glue. You can configure all these steps in the visual editor in AWS Glue Studio.