Published: 10 October 2022
Innovation through analytics and AI will be vital for enterprise success in 2023. To enable innovation at scale in a distributed environment, data and analytics technical professionals must develop trustworthy solutions and converge processes, models and technology for organizational growth.
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Enterprise data is proliferating over a very diverse data plane spanning on-premises, public cloud and edge. This diversity is complicating development of consistent analytics and representative AI models.
Disparate analytics domains are converging to deliver more insights more efficiently. By combining augmented data preparation, DSML and A&BI solutions, technical professionals are harnessing D&A investments, practices and processes to deliver effective decision support while rationalizing service sprawl.
Obstacles to enabling AI trust, scalability and operationalization are preventing organizations from harnessing AI’s business transformation potential. To succeed, AI initiatives require adequate data, transparency within prebuilt ML models, and an XOps framework integrating
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