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AWS Machine Learning

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AWS Machine Learning

13.12.2024

Answer questions from tables embedded in documents with Amazon Q Business | AWS Machine Learning Blog

Amazon Q Business launched support for tabular search, which you can use to extract answers from tables embedded in documents ingested in Amazon Q Business. Tabular search is a built-in feature in Amazon Q Business that works seamlessly across many domains, with no setup required from admin or end users. In this post, we ingest different types of documents that have tables and show you how Amazon Q Business responds to questions related to the data in the tables.

AWS Machine Learning

13.12.2024

Accelerate Amazon Redshift secure data use with Satori – Part 2 | AWS Big Data Blog

In this post, we continue from Accelerate Amazon Redshift secure data use with Satori – Part 1, and explain how Satori, an Amazon Redshift Ready partner, simplifies both the user experience of gaining access to data and the admin practice of granting and revoking access to data in Amazon Redshift. Satori enables both just-in-time and self-service access to data.

AWS Machine Learning

13.12.2024

Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt | AWS Big Data Blog

In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. dbt on Athena supports real-time queries, while dbt on Amazon Redshift handles complex queries, unifying the development language and significantly reducing the technical learning curve. Using a single dbt modeling language not only simplifies the development process but also automatically generates consistent data lineage information. This approach offers robust adaptability, easily accommodating changes in data structures.

AWS Machine Learning

13.12.2024

Understand the benefits of physical replication in Amazon RDS for PostgreSQL Blue/Green Deployments | AWS Database Blog

With the recent addition of physical replication as an option for RDS Blue/Green Deployments, you can overcome most of the limitations of logical replication. This makes physical replication particularly well-suited for use cases like minor version upgrades, schema changes (DDL operations) in the blue environment, and storage adjustments. In this post, we delve into the advantages of using physical replication in RDS for PostgreSQL blue/green deployments to simplify database operations and scale with application demands. We explore the key benefits of physical replication and provide a step-by-step guide to help you get started with this new capability.

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