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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. The following examples are also available in the sample notebook in the aws-samples GitHub repo for quick experimentation.

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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. A table in the Data Catalog is a metadata definition that represents the data in a data lake, and databases are used to organize these metadata tables. These mechanisms can be customized for your organization’s processes.

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

Corinium

Yes, definitely! All assets need to be optimally leveraged for maximum business value while also being protected from misuse, whether there was malicious intent or not, and this needs to be the responsibility of whomever is responsible for that asset in the company. What do you recommend to organisations to help them overcome these?

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Apply Modern CRM Dashboards & Reports Into Your Business – Examples & Templates

datapine

With a powerful dashboard maker , each point of your customer relations can be optimized to maximize your performance while bringing various additional benefits to the picture. Whether you’re looking at consumer management dashboards and reports, every CRM dashboard template you use should be optimal in terms of design.

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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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