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How A Data Catalog Enhances Data Risk Management

Alation

Alation joined with Ortecha , a data management consultancy, to publish a white paper providing insights and guidance to stakeholders and decision-makers charged with implementing or modernising data risk management functions. Download the complete white paper now. Or, read on for a brief summary.

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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

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Data Literacy for Responsible AI: Governance and Accountability

DataRobot

Throughout history, introducing innovations in fields like aviation and nuclear power to society required robust risk management frameworks. AI is no different, and by its nature, it demands a comprehensive approach to governance utilizing risk management. White Paper. Data Literacy for Responsible AI.

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The Foundations of a Modern Data-Driven Organisation: Change from Within (part 2 of 2)

Cloudera

A data-driven approach to talent management and development brings about greater transparency, reduced attrition and more effective training and enablement. A 2020 retention report by the Work Institute revealed that over 42 million employees in the US left their jobs voluntarily in 2019, and this trend appeared to be increasing.

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Post-Pandemic Enterprise Architecture Priorities

erwin

In a world where agility and innovation are highly valued, speed is a critical factor for success.COVID-19 forced many businesses to radically change their business models – or re-evaluate their business processes – shifting the focus of enterprise architects. Priority 3: Risk Management – Security and Compliance. erwin Evolve.

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The Future of RegTech for AI Governance

IBM Big Data Hub

” Examples of RegTech include chatbots that can advise on regulatory questions, cloud-based platforms for regulatory and compliance data management, and computer code that enables more automated processing of data relating to regulations [9]. 9] WEF “Regulatory Technology for the 21st Century” report [link]. [10] References. [1]

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Minding Your Models

DataRobot Blog

Using AI-based models increases your organization’s revenue, improves operational efficiency, and enhances client relationships. You need to know where your deployed models are, what they do, the data they use, the results they produce, and who relies upon their results. That requires a good model governance framework.

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