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Simplify data integration with AWS Glue and zero-ETL to Amazon SageMaker Lakehouse

AWS Big Data

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. We take care of the ETL for you by automating the creation and management of data replication. Glue ETL offers customer-managed data ingestion.

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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. For Role name , enter a role name (for this post, GlueJobRole-recipe-demo ).

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

AWS Big Data

Third, some services require you to set up and manage compute resources used for federated connectivity, and capabilities like connection testing and data preview arent available in all services. To solve for these challenges, we launched Amazon SageMaker Lakehouse unified data connectivity. An AWS Glue Data Catalog database.

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What Is Data Integrity?

Alation

But in the four years since it came into force, have companies reached their full potential for data integrity? But firstly, we need to look at how we define data integrity. What is data integrity? Many confuse data integrity with data quality. Is integrity a universal truth?

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Build data integration jobs with AI companion on AWS Glue Studio notebook powered by Amazon CodeWhisperer

AWS Big Data

AWS Glue provides different authoring experiences for you to build data integration jobs. Data scientists tend to run queries interactively and retrieve results immediately to author data integration jobs. This interactive experience can accelerate building data integration pipelines.

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Ingest data from Google Analytics 4 and Google Sheets to Amazon Redshift using Amazon AppFlow

AWS Big Data

Select the application type Web application , enter the name demo-google-aws, and provide URIs for Authorized JavaScript origins [link]. Select demo-google-aws. For this demo, you can upload the Nation Market segment file to your Google sheet before proceeding to the next steps. For Authorized redirect URIs , add [link].

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

While real-time data is processed by other applications, this setup maintains high-performance analytics without the expense of continuous processing. This agility accelerates EUROGATEs insight generation, keeping decision-making aligned with current data.

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