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Mike Ferguson

Independent Analyst

For Energy and Utilities companies to transition into data- and AI-driven entities, their success depends on efficiently integrating data from an expanding array of sources in a timely fashion. This necessity has evolved into a critical mission to establish a robust data foundation characterized by high quality, security, and compliance. This foundation serves as a catalyst for generating insights, recommendations, and predictions. By building upon this foundation, these companies can develop the necessary insights to modernize grid networks, adopt cost-effective renewable energy sources, enhance resilience, and improve grid health. This, in turn, enables them to offer superior services capable of withstanding the effects of climate change, while also providing more affordable energy to customers.

The central challenge lies in the continuously growing number of data sources and repositories spread across diverse hybrid, multi-cloud environments.

This paper looks at this challenge and explores how a logical data fabric powered by data virtualization can provide a platform to help solve it so that Energy and Utilities companies can shorten time to value, meet executive expectations and achieve their goal of becoming data-driven enterprises.

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