Analytics And Big Data For Accountants

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Analytics And Big Data For Accountants

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Author : Jim Lindell
language : en
Publisher: John Wiley & Sons
Release Date : 2020-12-03

Analytics And Big Data For Accountants written by Jim Lindell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-03 with Computers categories.

Why is big data analytics one of the hottest business topics today? This book will help accountants and financial managers better understand big data and analytics, including its history and current trends. It dives into the platforms and operating tools that will help you measure program impacts and ROI, visualize data and business processes, and uncover the relationship between key performance indicators. Key topics covered include: Evidence-based techniques for finding or generating data, selecting key performance indicators, isolating program effects Relating data to return on investment, financial values, and executive decision making Data sources including surveys, interviews, customer satisfaction, engagement, and operational data Visualizing and presenting complex results

Handbook Of Big Data And Analytics In Accounting And Auditing

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Author : Tarek Rana
language : en
Publisher: Springer Nature
Release Date : 2023-02-03

Handbook Of Big Data And Analytics In Accounting And Auditing written by Tarek Rana and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-03 with Business & Economics categories.

This handbook collects the most up-to-date scholarship, knowledge, and new developments of big data and data analytics by bringing together many strands of contextual and disciplinary research. In recent times, while there has been considerable research in exploring the role of big data, data analytics, and textual analytics in accounting, and auditing, we still lack evidence on what kinds of best practices academics, practitioners, and organizations can implement and use. To achieve this aim, the handbook focuses on both conventional and contemporary issues facing by academics, practitioners, and organizations particularly when technology and business environments are changing faster than ever. All the chapters in this handbook provide both retrospective and contemporary views and commentaries by leading and knowledgeable scholars in the field, who offer unique insights on the changing role of accounting and auditing in today’s data and analytics driven environment. Aimed at academics, practitioners, students, and consultants in the areas of accounting, auditing, and other business disciplines, the handbook provides high-level insight into the design, implementation, and working of big data and data analytics practices for all types of organizations worldwide. The leading scholars in the field provide critical evaluations and guidance on big data and data analytics by illustrating issues related to various sectors such as public, private, not-for-profit, and social enterprises. The handbook’s content will be highly desirable and accessible to accounting and non-accounting audiences across the globe.

Big Data Analytics

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Author : Greg Richins
language : en
Publisher:
Release Date : 2017

Big Data Analytics written by Greg Richins and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

Contrary to Frey and Osborne's (2013) prediction that the accounting profession faces extinction, we argue that accountants can still create value in a world of big data analytics. To advance this argument, we provide a conceptual framework based on structured/unstructured data and problem driven/exploratory analysis. We argue that accountants already excel at problem driven analysis of structured data, are well positioned to play a leading role in the problem driven analysis of unstructured data, and can support data scientists performing exploratory analysis on big data. Our argument rests on two pillars: accountants are familiar with structured data sets, easing the transition to working with unstructured data, and possess knowledge of business fundamentals. Thus, rather than replacing accountants, we argue that big data analytics complements accountants' skills and knowledge. However, educators, standard setters, and professional bodies must adjust their curricula, standards, and frameworks to accommodate the challenges of big data analytics.

Fourth Industrial Revolution And Business Dynamics

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Author : Nasser Rashad Al Mawali
language : en
Publisher: Springer Nature
Release Date : 2021-10-07

Fourth Industrial Revolution And Business Dynamics written by Nasser Rashad Al Mawali and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-07 with Business & Economics categories.

The book explains strategic issues, trends, challenges, and future scenario of global economy in the light of Fourth Industrial Revolution. It consists of insightful scientific essays authored by scholars and practitioners from business, technology, and economics area. The book contributes to business education by means of research, critical and theoretical reviews of issues in Fourth Industrial Revolution.

Data Analytics For Accounting

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Author : Vernon J. Richardson
language : en
Publisher:
Release Date : 2018-05-23

Data Analytics For Accounting written by Vernon J. Richardson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-23 with Accounting categories.

Big Data And Analytics In Accounting

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Author : AGOSTINI MARISA
language : en
Publisher: G Giappichelli Editore
Release Date : 2023-04-28

Big Data And Analytics In Accounting written by AGOSTINI MARISA and has been published by G Giappichelli Editore this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-28 with Business & Economics categories.

Digital technologies such as big data analytics (BDA) are being increasingly used by businesses to create economic and societal value (Ferraris et al., 2019; Constantiou and Kallinikos, 2015; Günther et al., 2017; Rana et al., 2023). As a consequence, academic literature has emphasised their “disruptive potential” for enhancing corporate sustainability performance (Etzion and Aragon-Correa, 2015), creating more equal and inclusive society (Secundo et al., 2017), fostering optimal reallocation of underutilized resources (Etter et al., 2019) and enabling more participatory and democratic forms of governance (Neu et al., 2019; Ojala et al., 2019; Uldam, 2018). Conversely, the advocates of the critical approach have raised concerns about digital technologies related to privacy and security threats (La Torre et al., 2018), limitations of autonomy and freedom (Andrew and Baker, 2019), labour exploitation (Fuchs, 2010), lack of algorithmic accountability (Martin, 2019), pervasive worker control (Chai and Scully, 2019), and ecological footprint (Corbett, 2018; Lucivero, 2020). Hence, the magnitude and pervasiveness of ethical, social and environmental risks that emerge as a consequence of user data collection, storage and algorithmic processing are imposing additional responsibility upon data processing companies. To this end, the extant literature offers three main reasons for why large technology companies still lack accountability for these consequences. First, the problem resides in the inherent power asymmetries between the companies and individual users that pre-empt the latter from holding the former accountable for their wrongdoings (Rosenblat and Stark, 2016; West, 2019). Such quasi-monopolistic concentration of power in the hands of internet corporations is exerted not only vis-a-vis individual consumers but also other organisations (i.e., suppliers, competitors) whose business survival depends on the services of the large companies (Flyverbom et al., 2019). Second, regulatory efforts in the data economy often take place post hoc (Nunan and Di Domenico, 2017) and do not adequately address the contemporary issues of digitalization (Royakkers et al., 2018). Until recently, a self-regulatory regime prevailed in technology regulation based on “soft” voluntary standards and principles which the large companies developed for themselves. Finally, wrongful practices become pervasive to the extent that the other actors take them for granted and stop questioning them (Ananny and Crawford, 2018). As a result, companies find themselves in a “dual” position in which they simultaneously need to harness the potential of BDA to generate economic and societal value on the one hand, while at the same time are required establish an effective mechanism for ensuring accountability for the negative consequences of data utilization on the other. Hence, from the accounting perspective, this raises three important questions as to (1) whether accounting scholars can explain the emergent issues with BDA using established accounting theories, (2) whether and, if so, how the processing of BD results in calls for wider organisational accountability and greater regulatory oversight and (3) how the value of BDA can be assessed from a financial accounting standpoint. The present manuscript aims to address these questions. Chapter 1 “Emerging technologies in accounting” reviews technologies that underlie the use of BDA in accounting, provide definitions, discuss their interdependencies and explain differences between different technologies, illustrating their current and potential applications. In particular, new sources of big data and their characteristics will be discussed; different analytical approaches will be reviewed. The principal goal of this chapter is to establish a clear terminology and introduce key concepts that are fundamental for understanding the role of BDA in accounting. Chapter 2 “Peculiar and established theories framing studies of BDA in accounting” examines whether and how accounting literature has rooted BDA issues inside theoretical frameworks in order to formulate new concepts and models, to support the adoption of further methods and approaches, to explain and root the solutions used in practice. Chapter 3 “Data Regulations in the European Union” provides the most recent overview of the legal frameworks and regulatory developments in the European Union with regards to the data collection, use, storage, processing and sharing. Starting with the General Data Protection Regulation (GDPR) implementation in 2018, the European Union is taking a pioneer role in data-related regulations globally, imposes greater obligations, stricter rules and accountability frameworks. The chapter provides business and competitive context to explains the nature of the problem each regulatory initiative seeks to address, provides a general overview of the legal provisions in the context of the theoretical research in law, information systems and accounting and concludes by critical assessment of the effectiveness of the regulation – enforced or proposed – in reaching its goals and formulates a series of recommendations for potential improvement. Chapter 4 “Assessing the Value of Big Data and Analytics: Issues, Opportunities and Challenges” assesses the value of data that derives, rather than from inherent conditions, from the possibility of generating insights and the actual use of the same (Ferraris et al., 2019; Günther et al., 2017). “Conclusion” summarizes key research findings useful to provide answers to the above listed three research questions.

Data Mining For Dummies

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Author : Meta S. Brown
language : en
Publisher: John Wiley & Sons
Release Date : 2014-09-29

Data Mining For Dummies written by Meta S. Brown and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-29 with Computers categories.

Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum. The ability to detect unseen patterns hidden in the numbers exhaustively generated by day-to-day operations allows savvy decision-makers to exploit every tool at their disposal in the pursuit of better business. By creating models and testing whether patterns hold up, it is possible to discover new intelligence that could change your business's entire paradigm for a more successful outcome. Data Mining for Dummies shows you why it doesn't take a data scientist to gain this advantage, and empowers average business people to start shaping a process relevant to their business's needs. In this book, you'll learn the hows and whys of mining to the depths of your data, and how to make the case for heavier investment into data mining capabilities. The book explains the details of the knowledge discovery process including: Model creation, validity testing, and interpretation Effective communication of findings Available tools, both paid and open-source Data selection, transformation, and evaluation Data Mining for Dummies takes you step-by-step through a real-world data-mining project using open-source tools that allow you to get immediate hands-on experience working with large amounts of data. You'll gain the confidence you need to start making data mining practices a routine part of your successful business. If you're serious about doing everything you can to push your company to the top, Data Mining for Dummies is your ticket to effective data mining.

Data Analytics For Business

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Author : Fenio Annansingh
language : en
Publisher: Routledge
Release Date : 2022-04-20

Data Analytics For Business written by Fenio Annansingh and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-20 with Business & Economics categories.

Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor’s manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.

Financial Data Analytics

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Author : Sinem Derindere Köseoğlu
language : en
Publisher: Springer Nature
Release Date : 2022-04-25

Financial Data Analytics written by Sinem Derindere Köseoğlu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-25 with Business & Economics categories.

​This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.

Customer Accounting

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Author : Massimiliano Bonacchi
language : en
Publisher: Springer
Release Date : 2018-11-04

Customer Accounting written by Massimiliano Bonacchi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-04 with Business & Economics categories.

This book is designed to meet the needs of CFOs, accounting and financial professionals interested in leveraging the power of data-driven customer insights in management accounting and financial reporting systems. While academic research in Marketing has developed increasingly sophisticated analytical tools, the role of customer analytics as a source of value creation from an Accounting and Finance perspective has received limited attention. The authors aim to fill this gap by blending interdisciplinary academic rigor with practical insights from real-world applications. Readers will find thorough coverage of advanced customer accounting concepts and techniques, including the calculation of customer lifetime value and customer equity for internal decision-making and for external financial reporting and valuation. Beyond a professional audience, the book will serve as ideal companion reading for students enrolled in undergraduate, graduate, or MBA courses.