The Sussex Garland - Taylor, James
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This scarce antiquarian book is a facsimile reprint of the original. Due to its age, it may contain imperfections such as marks, notations, marginalia and flawed pages. Because we believe this work is culturally important, we have made it available as part of our commitment for protecting, preserving, and promoting the world's literature in affordable, high quality, modern editions that are true to the original work.

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Produktbeschreibung
This scarce antiquarian book is a facsimile reprint of the original. Due to its age, it may contain imperfections such as marks, notations, marginalia and flawed pages. Because we believe this work is culturally important, we have made it available as part of our commitment for protecting, preserving, and promoting the world's literature in affordable, high quality, modern editions that are true to the original work.
Autorenporträt
James Taylor first came up with the phrase "Decision Management" in 2002. He has been focusing on the approach and the supporting technology stack for nearly 25 years and he is almost certainly the best-known proponent of the approach. While working at FICO he wrote a book on the topic with Neil Raden. Since then he has written Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics (IBM Press, 2012) and Digital Decisioning: Using Decision Management to Deliver Business Impact from Artificial Intelligence (JTonEDM Press, 2019), dozens of articles and white papers and several book chapters expanding and developing the core concepts. One of the original submitters of the Decision Model and Notation standard, he has been using decision modeling on client projects since 2011. He has designed and written effective development methodologies and developed several modeling tools, including one based on DMN - DecisionsFirst Modeler. As the founder of Decision Management Solutions, he works with clients to help them implement Decision Management and Decision Modeling so they can create more agile systems, operationalize their machine learning investments and successfully adopt AI.