Self-Service Data Analytics and Governance for Managers
Idioma: inglés
Editorial: John Wiley and Sons Inc, US, 2021
- Tapa dura
- Nuevo
Librería: Rarewaves.com USA, London, London, Reino UnidoRarewaves.com USA
Vendedor de AbeBooks desde 11 de junio de 2025
Condición: Nuevo
EUR 42,31
Cantidad disponible: 8 disponibles
Añadir al carritoDescripción del artículo del vendedor
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.…
N° de ref. del artículo LU-9781119773290
- Título
- Self-Service Data Analytics and Governance for Managers
- Autor
- Nathan E. Myers, Gregory Kogan
- Editorial
- John Wiley and Sons Inc, US
- Año de publicación
- 2021
- Estado
- New
- Encuadernación
- Hardback
- Idioma
- inglés
- ISBN 10
- 1119773296
- ISBN 13
- 9781119773290
- Peso del artículo
- 560 gramos
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.
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
NATHAN E. MYERS, MBA, CPA, Six Sigma Black Belt, has over 20 years in public accounting and investment banking experience at flagship organizations including Ernst & Young, Morgan Stanley, UBS Investment Bank, Credit Suisse, and JP Morgan. After receiving both his BS and MBA in Accounting from Indiana University, much of his career has been spent in finance functions as controller and as change manager for products such as FX spot, forwards, and options, securities lending, margin, and equity finance at global investment banks. In the recent past, his career has evolved from building scalable controls and delivering strategic technology change, to putting data analytics tooling into the hands of users to drive aggressive digital transformation.
GREGORY KOGAN, CPA,
is a professor of practice in accounting at Long Island University focusing on teaching undergraduate and graduate courses in accounting and finance. He has experience as an auditor at Ernst & Young and as a controller at Tiger Management. He received his MBA in Accounting from Rutgers Business School and a BS in Computer Science from Rutgers University.
“Acerca de” puede pertenecer a otra edición de este título.
Rarewaves.com USA
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Vendedor de AbeBooks desde 11 de junio de 2025
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