Self-Service Data Analytics and Governance for Managers - Hardcover

Myers, Nathan E.; Kogan, Gregory

 
9781119773290: Self-Service Data Analytics and Governance for Managers
Hardcover
ISBN 10: 1119773296 ISBN 13: 9781119773290
Verlag: Wiley, 2021

Inhaltsangabe

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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den 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.

Von der hinteren Coverseite

Help your firm's end-users make sense of self-service data analytics tools

In Self-Service Data Analytics and Governance for Managers, distinguished accountants and authors Nathan E. Myers and Gregory Kogan provide readers with a concise and insightful treatment of the importance of dedicated process governance standards for the use of self-service data analytics tools. The book invites Chief Financial Officers, managers, and auditors to proactively structure and implement an analytics governance framework to protect process stability, as data analytics outputs are increasingly relied upon throughout the organization.

With a focus throughout the book on the necessity for managers to structure the potential chaos that results from putting powerful and flexible application development capabilities directly into the hands of end users, Self-Service Data Analytics and Governance for Managers shows readers where and how to introduce and deploy prominant data analytics tools throughout their organization. Importantly, a fit-for-purpose foundational data analytics governance model is extended from the principles of mature control frameworks to promote process stability, risk management, and capture of ROI.

Ideal for analytics managers and process owners, Self-Service Data Analytics and Governance for Managers will also earn a place in the libraries of executives and auditors who demand the ability to rely on data analyses performed with self-service data analytics tools within their organizations or to assess the control structures that protect the value created by digital portfolios.

Aus dem Klappentext

The phenomena of data democratization and the widespread adoption of data analytics tools have resulted in the decentralization of application development, as users are equipped to both perform their own analyses on data sets and to automate manual spreadsheet processing steps in pursuit of control and efficiency gains. Many users, process owners, and managers are unfamiliar with the basic and crucial information governance techniques needed to maintain process control in this new environment.

Self-Service Data Analytics and Governance for Managers delivers an introduction to prominent data analytics tools and capabilities and demonstrates how these tools can be effectively deployed using real-world scenarios. The book provides finance, accounting, and operations managers with chapters on building tool familiarity, process discovery methodologies, matching tools with common use cases, and managing tool deployment in a way that bolsters control and stability of digital outputs. Throughout, the focus remains on establishing robust process governance standards as self-service digital tooling makes its way through an organization, equipping managers to structure the chaos that can result as development tools are placed into the hands of end users.

Perfect for process owners and operations managers, business intelligence and analytics managers, auditors, and Chief Financial Officers, Self-Service Data Analytics and Governance for Managers makes a compelling case for the necessity of laying the foundation for analytics governance early in the digital transformation journey. Further, the authors present an analytics governance framework that readers can adopt and adapt to protect their organizations, as increased reliance is placed on self-service data tools.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Wiley
Erscheinungsdatum
2021
Sprache
Englisch
ISBN 10 
1119773296
ISBN 13 
9781119773290
Einband
Gebundene Ausgabe
Auflage
1
Anzahl der Seiten
352
Kontakt zum Hersteller
Wiley-VCH GmbH
product_safety@wiley.com

Boschstrasse 12
Weinheim
69469
Deutschland