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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM).

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How to Bring Agile Innovation to Customer Success

Totango

An agile approach brings the full power of big data analytics to bear on customer success. Follow a clear plan on governance and decision making. This provides transparency and accountability and empowers a data-driven approach to customer success. Follow a Clear Plan on Governance and Decision making.

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Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker

AWS Machine Learning

However, implementing security, data privacy, and governance controls are still key challenges faced by customers when implementing ML workloads at scale. Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

Consider your security posture, governance, and operational excellence when assessing overall readiness to develop generative AI with LLMs and your organizational resiliency to any potential impacts. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

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Use Amazon SageMaker Model Card sharing to improve model governance

AWS Machine Learning

The framework that gives systematic visibility into ML model development, validation, and usage is called ML governance. During AWS re:Invent 2022, AWS introduced new ML governance tools for Amazon SageMaker which simplifies access control and enhances transparency over your ML projects.

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The 7 Deadly Sins of Customer Experience

CX Journey

Failing to outline a governance structure Without a governance structure in place, we perpetuate silo thinking and fail to achieve cross-functional alignment, involvement, and commitment. Because a governance structure outlines people, roles, and responsibilities when it comes to your customer experience strategy.

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­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account. SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Table formats provide a way to abstract data files as a table. Conclusion.

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