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1. |
Record Nr. |
UNINA9910810279203321 |
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Autore |
Jeavons Brad |
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Titolo |
Agile sales : delivering customer journeys of value and delight / / authored by Brad Jeavons ; edited by Emily Jeavons |
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Pubbl/distr/stampa |
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New York, New York ; ; Abingdon, Oxon : , : Routledge, , [2020] |
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©2020 |
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ISBN |
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1-000-05650-3 |
0-367-81691-1 |
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Descrizione fisica |
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1 online resource (xxxi, 170 pages) : illustrations |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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"The Agile philosophy has grown and achieved success initially through the Technology Design and Development teams of some of the world's largest organizations including Google, Netflix, and Microsoft. Recently, it has been adopted by the marketing departments of these organizations and others and new techniques are evolving for defining, engaging and providing customers amazing unique experiences. Sales teams are becoming disrupted by technology and the differentiated experiences marketing teams using Agile techniques are building for their customers online. Sales organizations have been looking for a way to avoid disruption and get back into the game with value. Agile is now starting to be adopted by sales teams, enabling these teams to revolutionize the way they engage customers with value and delighting experiences which result in greater value for the customer and themselves. This book outlines how Agile can help sales teams develop a culture of innovation focused on their customers. The book takes the reader through the customer buying journey (Agile technique) outlining tips and tricks that have come from Agile deployments within sales functions to help them get started. The key benefit for the reader is the introduction of a proven philosophy and techniques that will help them avoid disruption, elevate themselves from the commodity trap and |
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achieve success again. The book provides the reader insights into how to achieve sustainable change using real life case examples. The reader will also gain enjoyment and delight through the stories told and case examples provided"-- |
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2. |
Record Nr. |
UNINA9910890186103321 |
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Autore |
Tamura Yoshinobu <1950-> |
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Titolo |
Applied OSS Reliability Assessment Modeling, AI and Tools : Mathematics and AI for OSS Reliability Assessment / / by Yoshinobu Tamura, Shigeru Yamada |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (191 pages) |
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Collana |
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Springer Series in Reliability Engineering, , 2196-999X |
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Disciplina |
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Soggetti |
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Open source software |
Artificial intelligence |
Cooperating objects (Computer systems) |
Industrial engineering |
Production engineering |
Data protection |
Computers |
Open Source |
Artificial Intelligence |
Cyber-Physical Systems |
Industrial and Production Engineering |
Data and Information Security |
Hardware Performance and Reliability |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Open Source Software Reliability -- Stochastic Differential Equation Model for OSS Reliability Analysis -- Dimensional Stochastic Differential Equation Model for OSS Reliability Analysis -- Jump Diffusion Process |
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Model for OSS Reliability Analysis -- Cyclically Two Dimensional Stochastic Differential Equation Modeling -- Cyclically Two Dimensional Jump Diffusion Process Modeling -- Three Dimensional Tool Based on Noisy Model -- Deep Learning Method Based on fault big data Analysis for OSS Reliability Assessment -- Deep Learning Approach for OSS Reliability Assessment Considering Wiener Process -- Deep Learning Approach for OSS Reliability Assessment Considering Jump Diffusion Process -- Performance Illustrations of the Developed Application Tool Based on Deep Learning -- Exercise. |
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Sommario/riassunto |
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This textbook introduces the theory and application of open source software (OSS) reliability. The measurement and management of open source software are essential to produce and maintain quality and reliable systems while using open source software. This book describes the latest methods for the reliability assessment of open source software. It presents the state of the art of open source software reliability measurement and assessment based on stochastic modeling and deep learning approaches. It introduces several stochastic reliability analyses of OSS computing with application along with actual OSS project data. The book contains exercises to aid learning and is useful for graduate students and researchers. |
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