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Cloud-Based Supply Chain Risk Management Is Key To A Company’s Future

Smart Data Collective

There are many reasons that this is important if you want to minimize disruption to your supply chain in 2020. It’s important to know how to protect your own firm from spend risk, supply chain disruption while enhancing the company’s ability to thrive. It’s difficult to mitigate supply chain risk in the best of times.

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PODCAST: COVID19 | Redefining Digital Enterprises – Episode 7: The Impact of COVID-19 on Financial Services & Risk Management

bridgei2i

Episode 7: The Impact of COVID-19 on Financial Services & Risk. Management. The Impact of COVID-19 on Financial Services & Risk Management. As past data isn’t relevant anymore, current models aren’t going to work. PODCAST: COVID 19 | Redefining Digital Enterprises. Listening time: 12 minutes.

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Understanding the security shared responsibility model in an as-a-service world

CIO Business Intelligence

As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and risk management, with clear boundaries of shared responsibility. The security-shared-responsibility model provides a clear definition of the roles and responsibilities for security.”

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Sharing Responsibility for Data Security in the Cloud

CIO Business Intelligence

As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and risk management, with clear boundaries of shared responsibility. The security-shared-responsibility model provides a clear definition of the roles and responsibilities for security.”.

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

Cloudera

Collecting workforce data as a tool for talent management. A data-driven approach to talent management and development brings about greater transparency, reduced attrition and more effective training and enablement. These models are then used for anomaly detection or inferences about what will happen. . Risk Management.

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What to Do When AI Fails

O'Reilly on Data

Garbage in, garbage out still holds in 2020. This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk.

Risk 361
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Using Strategic Data Governance to Manage GDPR/CCPA Complexity

erwin

equivalent of GDPR] will not become effective until 2020, we believe that new developments in GDPR enforcement may influence the regulatory framework of the still fluid CCPA.”. Creating and automating a curated enterprise data catalog , complete with physical assets, data models, data movement, data quality and on-demand lineage.