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Balancing Innovation and Governance: The CDO’s Dilemma

N2Growth Blog

With the increasing importance of data and analytics that spans across several business areas, the need for a CDO who can adapt, innovate, and lead in this complex environment has grown significantly. The Intersection of Creativity and Regulatory Compliance In the 21st century, businesses are primarily driven by data-centric operations.

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Accelerating innovation with cloud-native apps on Microsoft Cloud

CIO

We spoke with Siddhartha Gupta, Global Head of Application Modernization on Azure at Tata Consultancy Services (TCS) , about this trend and what financial services organizations need to do to improve their capacity for agility and innovation. They must adopt innovations as soon as they become available.

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6 lessons to learn from the 60-year history of the modern mainframe

CIO

Dispelling misconceptions, mainframes are not relics of the past but beacons of innovation. Moreover, mainframes continue to evolve, integrating emerging technologies like AI and machine learning to meet the demands of tomorrow. Learn how Rocket Software can help you modernize without disruption today.

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CIOs eager to scale AI despite difficulty demonstrating ROI, survey finds

CIO

This transition has propelled AI and machine learning to the forefront, with 51% of CIOs identifying these technologies as among their most urgent priorities, alongside cybersecurity, highlighting their crucial role in driving organizational success. Today’s CIOs are working in a tornado of innovation.

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Pursuing A New Future of Innovation Through Digital Banking Strategy

CIO

At the centre of these changes are disruptive technologies like artificial intelligence, cloud computing, and machine learning, which are paving the way for new business models. Refining the balancing act of innovation and risk. However, this is also dependent on institutions meeting their regulatory compliance.

Banking 246
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Pursuing A New Future of Innovation Through Digital Banking Strategy

CIO

At the centre of these changes are disruptive technologies like artificial intelligence, cloud computing, and machine learning, which are paving the way for new business models. Refining the balancing act of innovation and risk. However, this is also dependent on institutions meeting their regulatory compliance.

Banking 246
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Why you should care about debugging machine learning models

O'Reilly Media - Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. 1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. 2] The Security of Machine Learning. [3] 6] See: Testing and Debugging Machine Learning Models. [7]