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

AWS Big Data

Amazon Athena provides interactive analytics service for analyzing the data in Amazon Simple Storage Service (Amazon S3). Amazon Redshift is used to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes. Table metadata is fetched from AWS Glue.

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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

We have enhanced data sharing performance with improved metadata handling, resulting in data sharing first query execution that is up to four times faster when the data sharing producers data is being updated. Industry-leading price-performance: Amazon Redshift launches RA3.large

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Alation and Salesforce partner on data governance for Data Cloud

CIO Business Intelligence

It will do this, it said, with bidirectional integration between its platform and Salesforce’s to seamlessly delivers data governance and end-to-end lineage within Salesforce Data Cloud. Additional to that, we are also allowing the metadata inside of Alation to be read into these agents.”

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Implement a custom subscription workflow for unmanaged Amazon S3 assets published with Amazon DataZone

AWS Big Data

Amazon DataZone , a data management service, helps you catalog, discover, share, and govern data stored across AWS, on-premises systems, and third-party sources. This approach streamlines data access while ensuring proper governance. You can publish the data asset so its now discoverable within the Amazon DataZone portal.

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Do I Need a Data Catalog?

erwin

The data catalog is a searchable asset that enables all data – including even formerly siloed tribal knowledge – to be cataloged and more quickly exposed to users for analysis. Three Types of Metadata in a Data Catalog. Technical Metadata. Operational Metadata. for analysis and integration purposes).

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Data governance in the age of generative AI

AWS Big Data

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. Data enrichment In addition, additional metadata may need to be extracted from the objects.