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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

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.

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How Data Analytics Improves Lead Management and Sales Results

Smart Data Collective

Reading: How Data Analytics Improves Lead Management and Sales Results Share Notification Font Resizer Aa Font Resizer Aa Search About Help Privacy Follow US © 2008-23 SmartData Collective. Contents Big Data Spending Is a Priority 1. A blog post from Edge Delta revealed that 97.2% All Rights Reserved.

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

AWS Big Data

Under Data sources , choose Amazon S3 , as shown in the following screenshot. Choose the Amazon S3 source node and enter the following values: S3 URI : s3://aws-blogs-artifacts-public/artifacts/BDB-4798/data/venue.csv Format : CSV Delimiter : , Multiline : Enabled Header : Disabled Leave the rest as default.

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Develop and monitor a Spark application using existing data in Amazon S3 with Amazon SageMaker Unified Studio

AWS Big Data

Organizations face significant challenges managing their big data analytics workloads. Data teams struggle with fragmented development environments, complex resource management, inconsistent monitoring, and cumbersome manual scheduling processes. Run the following code to develop your Spark application.

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Recap of Amazon Redshift key product announcements in 2024

AWS Big Data

Lakehouse allows you to use preferred analytics engines and AI models of your choice with consistent governance across all your data. At re:Invent 2024, we unveiled the next generation of Amazon SageMaker , a unified platform for data, analytics, and AI. Industry-leading price-performance: Amazon Redshift launches RA3.large

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Take manual snapshots and restore in a different domain spanning across various Regions and accounts in Amazon OpenSearch Service

AWS Big Data

Note: While using Postman or Insomnia to run the API calls mentioned throughout this blog, choose AWS IAM v4 as the authentication method and input your IAM credentials in the Authorization section. See blog post to understand how to use snapshot management policies to manage automated snapshot in OpenSearch Service.

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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

To populate source data: Run the following script on Query Editor to create the sample database DEMO_DB and tables inside DEMO_DB. To populate source data: Run the following script on Query Editor to create the sample database DEMO_DB and tables inside DEMO_DB. About the authors BP Yau is a Sr Partner Solutions Architect at AWS.