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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts.

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Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

AWS Machine Learning

This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. The data mesh is a modern approach to data management that decentralizes data ownership and treats data as a product.

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3 Ways to Make Customer Experience Governance Work for You

InMoment XI

Whether you’re just getting started on your customer experience (CX) initiative or hitting pause to see how things are going, the term “ customer experience governance ” is probably something you hear your team bring up all the time. But which governance style works best for you ? Three Ways to Approach CX Governance .

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Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

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Customer Experience Management: Optimizing Your Strategy for Financial Success

Speaker: Diane Magers, Founder and Chief Experience Officer at Experience Catalysts

To gain buy-in from the C-Suite and key stakeholders, it’s crucial to illustrate how Experience Management translates into clear, measurable business results. Transforming customer engagement, Voice of Customer (VoC) insights, and Journey Maps into tangible financial outcomes poses a significant challenge for most organizations.

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Unleash the power of generative AI with Amazon Q Business: How CCoEs can scale cloud governance best practices and drive innovation

AWS Machine Learning

This solution can serve as a valuable reference for other organizations looking to scale their cloud governance and enable their CCoE teams to drive greater impact. The challenge: Enabling self-service cloud governance at scale Hearst undertook a comprehensive governance transformation for their Amazon Web Services (AWS) infrastructure.

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Govern generative AI in the enterprise with Amazon SageMaker Canvas

AWS Machine Learning

This is crucial for compliance, security, and governance. In this post, we analyze strategies for governing access to Amazon Bedrock and SageMaker JumpStart models from within SageMaker Canvas using AWS Identity and Access Management (IAM) policies. We provide code examples tailored to common enterprise governance scenarios.

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How to Overcome the Pain Points of Your CRM

The promise of a CRM ( customer relationship management ) led organizations to believe each could digitally transform its businesses through tracking touchpoints throughout the buyer’s journey. However, as a company, sales stack, and database grow, it becomes difficult to uphold structure and governance to keep a CRM up-to-date.

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6 Killer Applications for Artificial Intelligence in the Customer Engagement Contact Center

If Artificial Intelligence for businesses is a red-hot topic in C-suites, AI for customer engagement and contact center customer service is white hot. This white paper covers specific areas in this domain that offer potential for transformational ROI, and a fast, zero-risk way to innovate with AI.