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Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes

AWS Big Data

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. You can use either the AWS Glue Data Catalog (recommended) or a Hive catalog for Iceberg tables.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments. This approach is not novel.

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Build a multi-Region and highly resilient modern data architecture using AWS Glue and AWS Lake Formation

AWS Big Data

The utility for cloning and experimentation is available in the open-sourced GitHub repository. This solution only replicates metadata in the Data Catalog, not the actual underlying data. This ensures that the data lake will still be functional in another Region if Lake Formation has an availability issue.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

Yes, definitely! The last 10+ years or so have seen Insurance become as data-driven as any vertical industry. For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks.

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