Analytics and Big Data for Accountants

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.

Author: Jim Lindell

Publisher: John Wiley & Sons

ISBN: 9781119784685

Category: Computers

Page: 224

View: 895


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

Exam Prep for Analytics and Big Data for Accountants

This book provides over 2,000 Exam Prep questions and answers to accompany the text Analytics and Big Data for Accountants Items include highly probable exam items: purpose, innovation, Chief information officer, survey, Transaction ...






View: 272


Advances in Accounting Education

CONCLUSION We describe a value-added data analytics case that can be
administered in a variety of accounting courses. The adaptable project ... An
accounting information systems perspective on data analytics and big data.
Journal of ...

Author: Thomas G. Calderon

Publisher: Emerald Group Publishing

ISBN: 9781787565395

Category: Business & Economics

Page: 240

View: 227


Advances in Accounting Education is a refereed, academic research publication whose purpose is to help meet the needs of faculty members interested in ways to improve accounting classroom instruction at the college and university level.

Contemporary Issues in Audit Management and Forensic Accounting

Different analysis types can be used in order to analyze Big Data for different
purposes. These are Descriptive Analytics, Diagnostic Analytics, Discovery
Analysis (Insight), and Predictive Analytics. Descriptive analysis, from an
accounting point ...

Author: Simon Grima

Publisher: Emerald Group Publishing

ISBN: 9781838676377

Category: Business & Economics

Page: 487

View: 743


In the 18 chapters in this volume of Contemporary Studies in Economic and Financial Analysis, expert contributors gather together to examine the extent and characteristics of forensic accounting, a field which has been practiced for many years, but is still not internationally regulated yet.

Analytics and Big Data The Davenport Collection 6 Items

In 1938 physicist Frank Benford made the same discovery in a much larger
amount of data than Newcomb. ... Many statisticians and accountants firmly
believe that Benford's Law is a relatively simple but powerful tool for identifying
potential ...

Author: Thomas H. Davenport

Publisher: Harvard Business Review Press

ISBN: 9781625277749

Category: Business & Economics

Page: 961

View: 731


The Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC. He is also an independent Senior Advisor to Deloitte Analytics.

Big Data Big Analytics

Emerging Business Intelligence and Analytic Trends for Today's Businesses
Michael Minelli, Michele Chambers, Ambiga ... transactional data; in the case of
banks, they saw detailed data about individual transactions within bank accounts.

Author: Michael Minelli

Publisher: John Wiley & Sons

ISBN: 9781118239155

Category: Business & Economics

Page: 224

View: 316


Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Fraud Analytics

Y FIRST job as a newly minted accounting graduate was—no surprise here—as
an auditor. I worked for a top accounting firm that was one of the “Big Eight” at the
time. ... The term “data analytics” wasn't even in the vernacular at that time.

Author: Delena D. Spann

Publisher: John Wiley & Sons

ISBN: 9781118282731

Category: Business & Economics

Page: 176

View: 259


Proven guidance for expertly using analytics in fraud examinations, financial analysis, auditing and fraud prevention Fraud Analytics thoroughly reveals the elements of analysis that are used in today's fraud examinations, fraud investigations, and financial crime investigations. This valuable resource reviews the types of analysis that should be considered prior to beginning an investigation and explains how to optimally use data mining techniques to detect fraud. Packed with examples and sample cases illustrating pertinent concepts in practice, this book also explores the two major data analytics providers: ACL and IDEA. Looks at elements of analysis used in today's fraud examinations Reveals how to use data mining (fraud analytic) techniques to detect fraud Examines ACL and IDEA as indispensable tools for fraud detection Includes an abundance of sample cases and examples Written by Delena D Spann, Board of Regent (Emeritus) for the Association of Certified Fraud Examiners (ACFE), who currently serves as Advisory Board Member of the Association of Certified Fraud Examiners, Board Member of the Education Task Force of the Association of Certified Anti-Money Laundering Specialists ASIS International (Economic Crime Council) and Advisory Board Member of the Robert Morris University (School of Business), Fraud Analytics equips you with authoritative fraud analysis techniques you can put to use right away.

Predictive Analytics Data Mining and Big Data

This information is required to generate bills,keep accounts upto date,and to
provide anaudit ofthe transactions thathave occurredbetween service providers
andtheir customers. Inrecent years organizations have become increasingly ...

Author: S. Finlay

Publisher: Springer

ISBN: 9781137379283

Category: Business & Economics

Page: 260

View: 619


This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.

Applied Business Analytics

Integrating Business Process, Big Data, and Advanced Analytics Nathaniel Lin.
smaller accounting or professional services accounts that stopped buying
hardware from IBM. In my experience, as more touches of customers are shifted
to ...

Author: Nathaniel Lin

Publisher: FT Press

ISBN: 9780133481532

Category: Business & Economics

Page: 288

View: 114


Bridge the gap between analytics and execution, and actually translate analytics into better business decision-making! Now that you've collected data and crunched numbers, Applied Business Analytics reveals how to fully apply the information and knowledge you've gleaned from quants and tech teams. Nathaniel Lin explains why "analytics value chains" often break due to organizational and cultural issues, and offers "in the trenches" guidance for overcoming these obstacles. You'll discover why a special breed of "analytics deciders" is indispensable for any organization that seeks to compete on analytics… how to become one of those deciders… and how to identify, foster, support, empower, and reward others to join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at all levels: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ — and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer Applied Business Analytics will be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics, including Chief Analytics Officers, Chief Data Officers, Chief Scientists, Chief Marketing Officers, Chief Risk Officers, Chief Strategy Officers, VPs of Analytics and/or Big Data, data scientists, business strategists, and line of business executives. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program, including candidates for INFORMS certification.

Beyond Big Data

ABBs (architectural building blocks), 48 accounts, as master data, 5 Activity Data
Hub engines, 68 Adaptive ... 169-170 analytics, 52-53 codes of conduct for
analytics practitioners, 220 cognitive analytics, 129 deriving confidence in results,
219 ...

Author: Martin Oberhofer

Publisher: IBM Press

ISBN: 9780133509816

Category: Computers

Page: 272

View: 804


Drive Powerful Business Value by Extending MDM to Social, Mobile, Local, and Transactional Data Enterprises have long relied on Master Data Management (MDM) to improve customer-related processes. But MDM was designed primarily for structured data. Today, crucial information is increasingly captured in unstructured, transactional, and social formats: from tweets and Facebook posts to call center transcripts. Even with tools like Hadoop, extracting usable insight is difficult—often, because it’s so difficult to integrate new and legacy data sources. In Beyond Big Data, five of IBM’s leading data management experts introduce powerful new ways to integrate social, mobile, location, and traditional data. Drawing on pioneering experience with IBM’s enterprise customers, they show how Social MDM can help you deepen relationships, improve prospect targeting, and fully engage customers through mobile channels. Business leaders and practitioners will discover powerful new ways to combine social and master data to improve performance and uncover new opportunities. Architects and other technical leaders will find a complete reference architecture, in-depth coverage of relevant technologies and use cases, and domain-specific best practices for their own projects. Coverage Includes How Social MDM extends fundamental MDM concepts and techniques Architecting Social MDM: components, functions, layers, and interactions Identifying high value relationships: person to product and person to organization Mapping Social MDM architecture to specific products and technologies Using Social MDM to create more compelling customer experiences Accelerating your transition to highly-targeted, contextual marketing Incorporating mobile data to improve employee productivity Avoiding privacy and ethical pitfalls throughout your ecosystem Previewing Semantic MDM and other emerging trends

Amazon Web Services for Mobile Developers

Ideally suited for high-performance databases, data mining and analysis,
Hadoop/Spark clusters, and other enterprise applications. R4 instances are not
eligible for AWS Free Tier accounts. R3 Memory optimized large xlarge 2xlarge
4xlarge ...

Author: Abhishek Mishra

Publisher: John Wiley & Sons

ISBN: 9781119377856

Category: Computers

Page: 792

View: 426


"Covers both iOS and Android devices"--Cover.

Big Data Analytics

This analysis creates a graph representing the corresponding relationships and
may also combine health histories with additional data ... extract critical business
information, or incrementally drain individual financial accounts while operating
completely under the radar. ... 10.7 GRAPH ANALYTICS ALGORITHMS AND
SOLUTION APPROACHES The graph model 97 Using Graph Analytics for Big

Author: David Loshin

Publisher: Elsevier

ISBN: 9780124186644

Category: Computers

Page: 142

View: 553


Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. Guides the reader in assessing the opportunities and value proposition Overview of big data hardware and software architectures Presents a variety of technologies and how they fit into the big data ecosystem

Big Data

For example, a uniform rule that a party need only preserve data after it was sued
or filed suit would create an opportunity ... Predictive analytics of employee
timekeeping records, productivity records, email accounts, and even Internet
search ...

Author: James R. Kalyvas

Publisher: CRC Press

ISBN: 9781466592377

Category: Business & Economics

Page: 240

View: 729


Big Data: A Business and Legal Guide supplies a clear understanding of the interrelationships between Big Data, the new business insights it reveals, and the laws, regulations, and contracting practices that impact the use of the insights and the data. Providing business executives and lawyers (in-house and in private practice) with an accessible primer on Big Data and its business implications, this book will enable readers to quickly grasp the key issues and effectively implement the right solutions to collecting, licensing, handling, and using Big Data. The book brings together subject matter experts who examine a different area of law in each chapter and explain how these laws can affect the way your business or organization can use Big Data. These experts also supply recommendations as to the steps your organization can take to maximize Big Data opportunities without increasing risk and liability to your organization. Provides a new way of thinking about Big Data that will help readers address emerging issues Supplies real-world advice and practical ways to handle the issues Uses examples pulled from the news and cases to illustrate points Includes a non-technical Big Data primer that discusses the characteristics of Big Data and distinguishes it from traditional database models Taking a cross-disciplinary approach, the book will help executives, managers, and counsel better understand the interrelationships between Big Data, decisions based on Big Data, and the laws, regulations, and contracting practices that impact its use. After reading this book, you will be able to think more broadly about the best way to harness Big Data in your business and establish procedures to ensure that legal considerations are part of the decision.

Digital Exhaust

What Everyone Should Know About Big Data, Digitization and Digitally Driven
Innovation Dale Neef. accounts perform at higher levels than those with fewer or
more accounts). ... own employees' social media activity).8 Unfortunately,
applying Big Data analytics and a little indifference to personal privacy and law,
these third ...

Author: Dale Neef

Publisher: Pearson Education

ISBN: 9780133838343

Category: Business & Economics

Page: 320

View: 760


Will "Big Data" supercharge the economy, tyrannize us, or both? Data Exhaust is the definitive primer for everyone who wants to understand all the implications of Big Data, digitally driven innovation, and the accelerating Internet Economy. Renowned digital expert Dale Neef clearly explains: What Big Data really is, and what's new and different about it How Big Data works, and what you need to know about Big Data technologies Where the data is coming from: how Big Data integrates sources ranging from social media to machine sensors, smartphones to financial transactions How companies use Big Data analytics to gain a more nuanced, accurate picture of their customers, their own performance, and the newest trends How governments and individual citizens can also benefit from Big Data How to overcome obstacles to success with Big Data – including poor data that can magnify human error A realistic assessment of Big Data threats to employment and personal privacy, now and in the future Neef places the Big Data phenomenon where it belongs: in the context of the broader global shift to the Internet economy, with all that implies. By doing so, he helps businesses plan Big Data strategy more effectively – and helps citizens and policymakers identify sensible policies for preventing its misuse. By conservative estimate, the global Big Data market will soar past $50 billion by 2018. But those direct expenses represent just the "tip of the iceberg" when it comes to Big Data's impact. Big Data is now of acute strategic interest for every organization that aims to succeed – and it is equally important to everyone else. Whoever you are, Data Exhaust tells you exactly what you need to know about Big Data – and what to do about it, too.

Statistical Techniques for Forensic Accounting

Understanding the Theory and Application of Data Analysis Saurav K. Dutta ...
Further, forensic accounting is an expanding practice for the Big Four and other
public accounting firms. This growth is attributable to the increased cost of fraud,
the ...

Author: Saurav K. Dutta

Publisher: FT Press

ISBN: 9780133133837

Category: Business & Economics

Page: 400

View: 841


Master powerful statistical techniques for uncovering fraud or misrepresentation in complex financial data. The discipline of statistics has developed sophisticated, well-accepted approaches for identifying financial fraud and demonstrating that it is deliberate. Statistical Techniques for Forensic Accounting is the first comprehensive guide to these tools and techniques. Leading expert Dr. Saurav Dutta explains their mathematical underpinnings, shows how to use them properly, and guides you in communicating your findings to other interested and knowledgeable parties, or assessing others' analyses. Dutta is singularly well-qualified to write this book: he has been engaged as an expert in many of the world's highest-profile financial fraud cases, including Worldcom, Global Crossing, Cendant, and HealthSouth. Here, he covers everything professionals need to know to construct and conduct valid and defensible statistical tests, perform analyses, and interpret others' analyses. Coverage includes: exploratory data analysis to identify the "Fraud Triangle" and other red flags… data mining tools, usage, and limitations… statistical terms and methods applicable to forensic accounting… relevant uncertainty and probability concepts… Bayesian analysis and networks… statistical inference, sampling, sample size, estimation, regression, correlation, classification, prediction, and much more. For all forensic accountants, auditors, investigators, and litigators involved with corporate financial reporting; and for all students interested in forensic accounting and related fields.


Emphasizing decision-making, this new edition features relevant topics such as data analytics as well as the time-tested features that have proven to be of most help to students.

Author: Paul D. Kimmel

Publisher: John Wiley & Sons

ISBN: 9781119494782

Category: Business & Economics

Page: 1488

View: 547


Accounting: Tools for Business Decision Making, 7th Edition is a two-semester financial and managerial accounting course designed to show students the importance of accounting in their everyday lives. Emphasizing decision-making, this new edition features relevant topics such as data analytics as well as the time-tested features that have proven to be of most help to students.

Accounting Principles

Accounting Principles, 14th Edition provides students with a clear overview of fundamental financial and managerial accounting concepts with a focus on learning the accounting cycle from the sole proprietor perspective.

Author: Jerry J. Weygandt

Publisher: John Wiley & Sons

ISBN: 9781119707110

Category: Business & Economics

Page: 1472

View: 371


Accounting Principles, 14th Edition provides students with a clear overview of fundamental financial and managerial accounting concepts with a focus on learning the accounting cycle from the sole proprietor perspective. Through a primary review of accounting transactions, integrated real-world examples, and a variety of practice opportunities, students develop a thorough understanding of how to apply accounting principles and techniques in practice. Students work through an entire program that builds their mastery of accounting concepts with an emphasis on decision making and key data analysis skills appropriate at the introductory level that keeps them engaged and better prepared to connect the classroom to the real world.

Analysis of TCP Performance in Data Center Networks

TCP alone accounts for almost 82% of packets and about 91% of the byte count
on the Web [13]. TCP also accounts for ... The senders, upon receiving the
request, concurrently transmit a large amount of data to the receiver. The data
from all ...

Author: Santosh Kulkarni

Publisher: Springer Science & Business Media

ISBN: 9781461478614

Category: Technology & Engineering

Page: 87

View: 897


This book addresses the need to improve TCP’s performance inside data centers by providing solutions that are both practical and backward compatible with standard TCP versions. The authors approach this challenge first by deriving an analytical model for TCP’s performance under typical data center workload traffic. They then discuss some solutions that are designed to improve TCP performance by either proactively detecting network congestion through probabilistic retransmission or by avoiding timeout penalty through dynamic resizing of TCP segments. Experimental results show that each of techniques discussed outperforms standard TCP inside a data center.

Enterprise Analytics

Optimize Performance, Process, and Decisions Through Big Data Thomas H.
Davenport ... By many accounts, international airlines found the data useful for
such purposes as market share analyses, network planning and optimization,
fleet ...

Author: Thomas H. Davenport

Publisher: FT Press

ISBN: 9780133039467

Category: Business & Economics

Page: 304

View: 555


Normal 0 false false false MicrosoftInternetExplorer4 The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management Organizations are capturing exponentially larger amounts of data than ever, and now they have to figure out what to do with it. Using analytics, you can harness this data, discover hidden patterns, and use this knowledge to act meaningfully for competitive advantage. Suddenly, you can go beyond understanding “how, when, and where” events have occurred, to understand why – and use this knowledge to reshape the future. Now, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) have brought together the latest techniques, best practices, and research on analytics in a single primer for maximizing the value of enterprise data. Enterprise Analytics is today’s definitive guide to analytics strategy, planning, organization, implementation, and usage. It covers everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. The authors offer specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions. They support their powerful techniques with many real-world examples, including chapter-length case studies from healthcare, retail, and financial services. Enterprise Analytics will be an invaluable resource for every business and technical professional who wants to make better data-driven decisions: operations, supply chain, and product managers; product, financial, and marketing analysts; CIOs and other IT leaders; data, web, and data warehouse specialists, and many others.

Business Analytics with Management Science Models and Methods

Chapter 7, “Business Analytics with Shipment Models,” discusses the use of
mathematical programming models in shipment and logistics. Decision ...
intraorganizational, and interorganizational shipments and accounts for a
significant part of the costs of products and services. ... But there are also simple
LP models with only a few constraints and decision variables that use large input
(Big Data) sets.

Author: Arben Asllani

Publisher: FT Press

ISBN: 9780133760668

Category: Business & Economics

Page: 400

View: 843


Master decision modeling and analytics through realistic examples, intuitive explanations, and tested Excel templates. Business Analytics with Management Science has been designed to help students, practitioners and managers use business analytics to improve decision-making systems. Unlike previous books, it emphasizes the application of practical management science techniques in business analytics. Drawing on 20+ years of teaching and consulting experience, Dr. Arben Asllani introduces decision analytics through realistic examples and intuitive explanations – not complex formulae and theoretical definitions. Throughout, Asllani helps practitioners focus more on the crucial input-output aspects of decision making – and less upon internal model complexities that can usually be "delegated" to software.