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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. You can find full results from the survey in the free report “Evolving Data Infrastructure”.). Data Platforms.

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Why you should care about debugging machine learning models

O'Reilly on Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes.

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The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 304
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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.

IoT 111
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Scaling RISE with SAP data and AWS Glue

AWS Big Data

The SAP OData connector supports both on-premises and cloud-hosted (native and SAP RISE) deployments. By using the AWS Glue OData connector for SAP, you can work seamlessly with your data on AWS Glue and Apache Spark in a distributed fashion for efficient processing.

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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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Demystify data sharing and collaboration patterns on AWS: Choosing the right tool for the job

AWS Big Data

Let’s briefly describe the capabilities of the AWS services we referred above: AWS Glue is a fully managed, serverless, and scalable extract, transform, and load (ETL) service that simplifies the process of discovering, preparing, and loading data for analytics. To incorporate this third-party data, AWS Data Exchange is the logical choice.

Sales 115