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... There are a plethora of platforms available for building AI agents, but many lack enterprise-ready foundations. Data and analytics leaders should identify and leverage new DSML platform capabilities to build, deploy, and manage AI agents for real business impact. Overview Strategic Planning Assumption ...
... Access Insights Already a Gartner client? CFOs recognize the need for datascience roles, but can easily get overwhelmed by the range of positions and skills that can encompass these roles. CFOs must first focus their datascience talent strategy around finance’s current AI maturity, then combine build ...
... Insights Already a Gartner client? AI is rewriting the rules of analytics. Dashboards are giving way to AI-native, perceptive intelligence, while datascience and ML teams evolve to support AI at scale. D&A leaders must rethink strategies, operating models, skills, and governance to thrive in an agent- ...
... Datascience talent is infamously difficult to find. Rather than hiring externally, Eastman took analysts from across the business and protected their time so they could learn datascience. This case study shows data and analytics leaders how to build their own datascience team with resources they already ...
Analyst(s): Chief Data and Analytics Officer Research Team
... derived from a background in financial statement audit, internal audit, data analytics, IT risk management and analytics education. Experience across all lines of defense. Audit Data Analytics Audit Data Analytics Strategy DataScience Education Audit Analytics Infrastructure Analytics Tools Audit Function ...
... techniques and practices, AI Engineering and next-generation decision intelligence systems. Mr. Brethenoux has extensive experience in the domains of AI, datascience and cognitive computing. Prior to rejoining Gartner, he was IBM Director of Machine Learning & Analytics Strategy. Prior to IBM, he was VP of Corporate ...
... Gartner First Takes Fresh insights on emerging trends Buyers of datascience and machine learning platforms struggle to identify key differentiators between platform capabilities. The head of datascience and AI can use this curated research as a starting point to examine DSML platform options and criteria ...
... Datascience talent is infamously difficult to find. Rather than hiring externally, Eastman took analysts from across the business and protected their time so they could learn datascience. This case study shows data and analytics leaders how to build their own datascience team with resources they already ...
Analyst(s): Chief Data and Analytics Officer Research Team