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The Right Stuff: The Role of MLOps in AI Success

CIO

Interestingly, many companies do just that, creating a disconnect between data science teams and IT/DevOps when it comes to AI development. Data scientists would really love to just build models and do real core data science. This approach can help companies bridge the divide between the data and IT sides. “A

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6 generative AI hazards IT leaders should avoid

CIO

That’s what eight out of 10 IT staff said in last year’s State of DevOps Automation Report , and up to just over 90% in the 2023 State of DevOps Automation and AI study. Initial concerns have been about the confidentiality of enterprise data, but reputational damage should also be a priority.

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Analytics Maturity Model: Levels, Technologies, and Applications

Altexsoft

Sometimes, a data or business analyst is employed to interpret available data, or a part-time data engineer is involved to manage the data architecture and customize the purchased software. At this stage, data is siloed, not accessible for most employees, and decisions are mostly not data-driven.

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