Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 26,81
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Librería: INDOO, Avenel, NJ, Estados Unidos de America
EUR 29,15
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 27,91
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Idioma: Inglés
Publicado por John Wiley and Sons Inc, US, 2021
ISBN 10: 1119773296 ISBN 13: 9781119773290
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 34,84
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Añadir al carritoHardback. Condición: New. Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands.
Idioma: Inglés
Publicado por John Wiley and Sons Inc, US, 2021
ISBN 10: 1119773296 ISBN 13: 9781119773290
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
EUR 36,19
Cantidad disponible: 8 disponibles
Añadir al carritoHardback. Condición: New. Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands.
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 256 pages. 9.21x6.42x1.34 inches. In Stock.
Librería: Ubiquity Trade, Miami, FL, Estados Unidos de America
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Idioma: Inglés
Publicado por John Wiley and Sons Inc, US, 2021
ISBN 10: 1119773296 ISBN 13: 9781119773290
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
EUR 37,94
Cantidad disponible: 8 disponibles
Añadir al carritoHardback. Condición: New. Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands.
Idioma: Inglés
Publicado por John Wiley and Sons Inc, US, 2021
ISBN 10: 1119773296 ISBN 13: 9781119773290
Librería: Rarewaves.com UK, London, Reino Unido
EUR 32,18
Cantidad disponible: 1 disponibles
Añadir al carritoHardback. Condición: New. Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands.