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Revolutionizing data management: Trends driving security, scalability, and governance in 2025

CIO

From data masking technologies that ensure unparalleled privacy to cloud-native innovations driving scalability, these trends highlight how enterprises can balance innovation with accountability. With machine learning, these processes can be refined over time and anomalies can be predicted before they arise.

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Lessons learned turning machine learning models into real products and services

O'Reilly Media - Data

Today, just 15% of enterprises are using machine learning, but double that number already have it on their roadmaps for the upcoming year. However, in talking with CEOs looking to implement machine learning in their organizations, there seems to be a common problem in moving machine learning from science to production.

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How today’s enterprise architect juggles strategy, tech and innovation

CIO

tagging, component/application mapping, key metric collection) and tools incorporated to ensure data can be reported on sufficiently and efficiently without creating an industry in itself! to identify opportunities for optimizations that reduce cost, improve efficiency and ensure scalability.

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Machine Learning for Fraud Detection in Streaming Services

Netflix Tech

Data analysis and machine learning techniques are great candidates to help secure large-scale streaming platforms. Although model-based anomaly detection approaches are more scalable and suitable for real-time analysis, they highly rely on the availability of (often labeled) context-specific data.

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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning - AI

Model monitoring of key NLP metrics was incorporated and controls were implemented to prevent unsafe, unethical, or off-topic responses. The flexible, scalable nature of AWS services makes it straightforward to continually refine the platform through improvements to the machine learning models and addition of new features.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. Although the implementation is straightforward, following best practices is crucial for the scalability, security, and maintainability of your observability infrastructure.

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Scaling Media Machine Learning at Netflix

Netflix Tech

We have been leveraging machine learning (ML) models to personalize artwork and to help our creatives create promotional content efficiently. Case study: scaling match cutting using the media ML infra The Media Machine Learning Infrastructure is empowering various scenarios across Netflix, and some of them are described here.