Remove Data Lake Remove Experimentation Remove Optimization
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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

It has far-reaching implications as to how such applications should be developed and by whom: ML applications are directly exposed to the constantly changing real world through data, whereas traditional software operates in a simplified, static, abstract world which is directly constructed by the developer. This approach is not novel.

IT 364
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. She has been heavily involved in the Data Sharing Project, focusing on the implementation of Amazon DataZone into EUROGATEs IT environment.

IoT 111
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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt

AWS Big Data

Amazon Athena offers serverless, flexible SQL analytics for one-time queries, enabling direct querying of Amazon Simple Storage Service (Amazon S3) data for rapid, cost-effective instant analysis. In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift.

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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. This property is set to true by default. availability.

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Your New Cloud for AI May Be Inside a Colo

CIO Business Intelligence

Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex. The cloud is great for experimentation when data sets are smaller and model complexity is light.

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Einstein Studio 1: What it is and what to expect

CIO Business Intelligence

With this platform, Salesforce seeks to help organizations apply the cleverness of LLMs to the customer data they have squirreled away in Salesforce data lakes in the hopes of selling more. Salesforce is pushing the idea that Einstein 1 is a vehicle for experimentation and iteration. The data is there.

Data Lake 119