Data Strategy for the Ultimate AI Lab

As public and private sector leaders develop data, cloud, and Artificial Intelligence (AI) / Machine Learning (ML) strategies, the need for a unified framework has never been more apparent.

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Developed strategies in data, cloud, and Artificial (AI) / Machine Learning (ML) naturally overlap, presenting challenges spanning strategy development, continuous delivery, and operations. Organizations and their perspective data, cloud, and AI divisions need to coalesce around a unified vision, strategy, and execution plan while bringing rigorous engineering practices and a scientific approach to continuously deliver solutions that shorten the time to customer value (TTCV) and build a sustained competitive advantage.

 A data strategy is critical to aligning data-related needs and planned usage to priority enterprise goals. The strategy’s goals and objectives serve as the framework for subsequent implementation of plans and actions.

This white paper explores some of the challenges and necessary considerations when developing, maintaining, and governing data solutions. Accordingly, this series also includes the AI Strategy for the Ultimate AI LabCloud Strategy for the Ultimate AI Lab, and Foundations for the Ultimate AI Lab white papers, which explore the implementation of each respective strategy, along with a culminating business case for strategy integration: The Ultimate AI Lab.

Thank you to Charles Landau and Stephanie Ling for contributing to this paper. 

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