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The Business Value of Data Virtualization is Time (and Speed)

Data Virtualization

“Technology changes, economic laws do not.” This is one of the most important concepts highlighted in 1994 by Carl Shapiro and Hal R. Varian in their book Information Rules. This simple idea describes the importance of the real effectiveness of.

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AI adoption accelerates as enterprise PoCs show productivity gains

CIO Business Intelligence

Like other CIOs, Katrina Redmond has been inundated with opportunities to deploy AI that promise to speed business and operations processes, and optimize workflows. To be successful, an AI proof of concept (PoC) project also needs to make good business sense, says CIO Vikram Nafde, CIO at Connecticut-based Webster Bank.

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IT leaders explore footing amid shifting needs and the AI power struggle

CIO Business Intelligence

Some even implemented their own virtual personal assistants (VPAs), which included at least natural language processing—and sometimes more intelligence than that. This immediately opened the potential to tap more value from legacy systems.” Suddenly, for the first time, the power of AI was accessible to non-technologists.

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Using generative AI to accelerate product innovation

IBM Big Data Hub

Stacking strong data management, predictive analytics and GenAI is foundational to taking your product organization to the next level. Addressing customer inquiries with an AI-driven chatbot ChatGPT distinguished itself as the first publicly accessible GenAI-powered virtual chatbot.

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Gen AI: Should you build or buy?

CIO Business Intelligence

CIOs should take a build and buy approach to accelerate gen AI adoption and capture the value it brings to their business. It’s an approach, says Ramamurthy, that many CIOs already take with broader tech strategy: Build the solutions that provide competitive advantage to your business, and outsource the rest.

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CIOs still grapple with what gen AI can do for the enterprise

CIO Business Intelligence

And for business users, it will surpass what Microsoft did for workforce productivity.” One of the first use cases of artificial intelligence in many companies, including both Michelin and Albemarle, was predictive maintenance, which at its most basic level is an algorithm trained on data collected by sensors.

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Start DataOps Today with ‘Lean DataOps’

DataKitchen

Data organizations don’t always have the budget or schedule required for DataOps when conceived as a top-to-bottom, enterprise-wide transformational change. DataOps can and should be implemented in small steps that complement and build upon existing workflows and data pipelines. Figure 1 shows the four phases of Lean DataOps.

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