5 Steps CIOs Can Take to Sustainable IT

5_steps_CIOs
The world faces formidable sustainability challenges and is increasingly turning to technology in search of solutions. The same global trend is also materializing in enterprises, which seek to advance their sustainability goals with technology investment. At the same time, there is a growing pressure to make technology itself more sustainable. This complimentary webinar, one of a four-part series, will explore the role of the CIO and the IT organization in the new strategic environment. We share the five steps CIOs need to take to achieve sustainable IT.
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OTHER ON-DEMAND WEBINARS

All Roads Lead to DevOps

xebialabs

Different situations, different teams, and different requirements call for different ways to approach your software delivery initiatives. Your road to success might mean taking the highway or a shortcut to get the job done. However, regardless of your cloud, container, security, compliance, or ITSM goals, all roads eventually lead to the same destination…DevOps.
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Incorporating Security into Web Application Development

While the concept of incorporating security into the software development lifecycle (SDLC) is not new, a staggering number of enterprises still only run automated scanning on deployed applications, not realizing the whole potential of modern scanning solutions. In this webinar, we will focus on moving security testing into the earlier stages of the software development lifecycle in order to eliminate web security issues as soon as possible.
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Unlock use cases with democratized data and AI platforms

Adopting artificial intelligence (AI) has become a strategic imperative. Early adopters are achieving massive returns, while those who wait run the risk of falling behind. In order to empower more decision-makers across business units, it is essential for organizations to embrace democratization of both data and AI.Companies seeking to democratize the entire AI lifecycle are mobilizing new data. However, a key challenge is that internal data is often siloed and restricted, which makes discovery and deployment harder than ever.
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Opening the “Black Box”: Model Validation in the Age of AI

DataRobot

Recent technological advancements have accelerated the integration of AI and machine learning models into more and more processes. However, model risk must be effectively managed. If left unchecked, the consequences of model risk can be severe. AI and machine learning models require constant monitoring and effective validation – this is not only a regulatory requirement in many industries but also sound business practice. On this webinar, Seph Mard, Head of Model Risk Management at DataRobot and Peter Simon, Financial Markets Practice Data Scientist at DataRobot will present the cornerstones of effective modern model risk management in the age of AI and machine learning. It provides.
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