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Automating the Automators: Shift Change in the Robot Factory

O'Reilly on Data

Think about what the model results tell you: “Maybe a random forest isn’t the best tool to split this data, but XLNet is.” ” If none of your models performed well, that tells you that your dataset–your choice of raw data, feature selection, and feature engineering–is not amenable to machine learning.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

The following requirements were essential to decide for adopting a modern data mesh architecture: Domain-oriented ownership and data-as-a-product : EUROGATE aims to: Enable scalable and straightforward data sharing across organizational boundaries. Eliminate centralized bottlenecks and complex data pipelines.

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CIOs are rethinking how they use public cloud services. Here’s why.

CIO Business Intelligence

Theres a renewed focus on on-premises, on-premises private cloud, or hosted private cloud versus public cloud, especially as data-heavy workloads such as generative AI have started to push cloud spend up astronomically, adds Woo. Id be cautious about going down the path of private cloud hosting or on premises, says Nag.

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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

Third, some services require you to set up and manage compute resources used for federated connectivity, and capabilities like connection testing and data preview arent available in all services. To solve for these challenges, we launched Amazon SageMaker Lakehouse unified data connectivity. For Add data source , choose Add connection.

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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

Within seconds of transactional data being written into Amazon Aurora (a fully managed modern relational database service offering performance and high availability at scale), the data is seamlessly made available in Amazon Redshift for analytics and machine learning. Enter a name for your repo, such as dbt-zeroetl.

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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

By treating the data as a product, the outcome is a reusable asset that outlives a project and meets the needs of the enterprise consumer. Consumer feedback and demand drives creation and maintenance of the data product. Her special areas of interest are data analytics, machine learning/AI, and application modernization.

Metadata 105
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Unlock scalable analytics with a secure connectivity pattern in AWS Glue to read from or write to Snowflake

AWS Big Data

By using AWS Glue to integrate data from Snowflake, Amazon S3, and SaaS applications, organizations can unlock new opportunities in generative artificial intelligence (AI) , machine learning (ML) , business intelligence (BI) , and self-service analytics or feed data to underlying applications.

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