Remove Data Warehouse Remove Metadata Remove Reference
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Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Table metadata is fetched from AWS Glue. The generated Athena SQL query is run.

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

AWS Big Data

You can learn how to query Delta Lake native tables through UniForm from different data warehouses or engines such as Amazon Redshift as an example of expanding data access to more engines. Both Delta Lake and Iceberg metadata files reference the same data files. in Delta Lake public document. Appendix 1.

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Write queries faster with Amazon Q generative SQL for Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed, AI-powered cloud data warehouse that delivers the best price-performance for your analytics workloads at any scale. It enables you to get insights faster without extensive knowledge of your organization’s complex database schema and metadata. Your data is not shared across accounts.

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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. For more examples and references to other posts, refer to the following GitHub repository.

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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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Accelerate SQL code migration from Google BigQuery to Amazon Redshift using BladeBridge

AWS Big Data

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. times better price performance than other cloud data warehouses.

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Seamless integration of data lake and data warehouse using Amazon Redshift Spectrum and Amazon DataZone

AWS Big Data

Unifying these necessitates additional data processing, requiring each business unit to provision and maintain a separate data warehouse. This burdens business units focused solely on consuming the curated data for analysis and not concerned with data management tasks, cleansing, or comprehensive data processing.

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