| data analysis for accountants: Data Analytics for Accounting Vernon J. Richardson, Ryan Teeter, Katie L. Terrell, 2018-05-23 |
| data analysis for accountants: Analytics and Big Data for Accountants Jim Lindell, 2020-10-29 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 |
| data analysis for accountants: Quantitative Data Analysis Willem Mertens, Amedeo Pugliese, Jan Recker, 2016-09-29 This book offers postgraduate and early career researchers in accounting and information systems a guide to choosing, executing and reporting appropriate data analysis methods to answer their research questions. It provides readers with a basic understanding of the steps that each method involves, and of the facets of the analysis that require special attention. Rather than presenting an exhaustive overview of the methods or explaining them in detail, the book serves as a starting point for developing data analysis skills: it provides hands-on guidelines for conducting the most common analyses and reporting results, and includes pointers to more extensive resources. Comprehensive yet succinct, the book is brief and written in a language that everyone can understand - from students to those employed by organizations wanting to study the context in which they work. It also serves as a refresher for researchers who have learned data analysis techniques previously but who need a reminder for the specific study they are involved in. |
| data analysis for accountants: Data Mining For Dummies Meta S. Brown, 2014-09-04 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 analysis for accountants: Statistical Techniques for Forensic Accounting Saurav K. Dutta, 2013 Fraud or misrepresentation often creates patterns of error within complex financial data. The discipline of statistics has developed sophisticated techniques and well-accepted tools for uncovering these patterns and demonstrating that they are the result of deliberate malfeasance. Statistical Techniques for Forensic Accounting is the first comprehensive guide to these tools and techniques: understanding their mathematical underpinnings, using them properly, and effectively communicating findings to non-experts. Dr. Saurav Dutta, one of the field's leading experts, has been engaged as an expert in many of the world's highest-profile fraud cases, including Worldcom, Global Crossing, Cendant, and HealthSouth. Now, he covers everything forensic accountants, auditors, investigators, and litigators need to know to use these tools and interpret others' use of them. Coverage includes: Exploratory data analysis: identifying the Fraud Triangle and other red flags Data mining: tools, usage, and limitations Traditional statistical terms and methods applicable to forensic accounting Uncertainty and probability theories and their forensic implications Bayesian analysis and networks Statistical inference, sampling, sample size, estimation, regression, correlation, classification, and prediction How to construct and conduct valid and defensible statistical tests How to articulate and effectively communicate findings to other interested and knowledgeable parties |
| data analysis for accountants: Forensic Analytics Mark J. Nigrini, 2011-05-12 Discover how to detect fraud, biases, or errors in your data using Access or Excel With over 300 images, Forensic Analytics reviews and shows how twenty substantive and rigorous tests can be used to detect fraud, errors, estimates, or biases in your data. For each test, the original data is shown with the steps needed to get to the final result. The tests range from high-level data overviews to assess the reasonableness of data, to highly focused tests that give small samples of highly suspicious transactions. These tests are relevant to your organization, whether small or large, for profit, nonprofit, or government-related. Demonstrates how to use Access, Excel, and PowerPoint in a forensic setting Explores use of statistical techniques such as Benford's Law, descriptive statistics, correlation, and time-series analysis to detect fraud and errors Discusses the detection of financial statement fraud using various statistical approaches Explains how to score locations, agents, customers, or employees for fraud risk Shows you how to become the data analytics expert in your organization Forensic Analytics shows how you can use Microsoft Access and Excel as your primary data interrogation tools to find exceptional, irregular, and anomalous records. |
| data analysis for accountants: Forensic Analytics Mark J. Nigrini, 2020-04-20 Become the forensic analytics expert in your organization using effective and efficient data analysis tests to find anomalies, biases, and potential fraud—the updated new edition Forensic Analytics reviews the methods and techniques that forensic accountants can use to detect intentional and unintentional errors, fraud, and biases. This updated second edition shows accountants and auditors how analyzing their corporate or public sector data can highlight transactions, balances, or subsets of transactions or balances in need of attention. These tests are made up of a set of initial high-level overview tests followed by a series of more focused tests. These focused tests use a variety of quantitative methods including Benford’s Law, outlier detection, the detection of duplicates, a comparison to benchmarks, time-series methods, risk-scoring, and sometimes simply statistical logic. The tests in the new edition include the newly developed vector variation score that quantifies the change in an array of data from one period to the next. The goals of the tests are to either produce a small sample of suspicious transactions, a small set of transaction groups, or a risk score related to individual transactions or a group of items. The new edition includes over two hundred figures. Each chapter, where applicable, includes one or more cases showing how the tests under discussion could have detected the fraud or anomalies. The new edition also includes two chapters each describing multi-million-dollar fraud schemes and the insights that can be learned from those examples. These interesting real-world examples help to make the text accessible and understandable for accounting professionals and accounting students without rigorous backgrounds in mathematics and statistics. Emphasizing practical applications, the new edition shows how to use either Excel or Access to run these analytics tests. The book also has some coverage on using Minitab, IDEA, R, and Tableau to run forensic-focused tests. The use of SAS and Power BI rounds out the software coverage. The software screenshots use the latest versions of the software available at the time of writing. This authoritative book: Describes the use of statistically-based techniques including Benford’s Law, descriptive statistics, and the vector variation score to detect errors and anomalies Shows how to run most of the tests in Access and Excel, and other data analysis software packages for a small sample of the tests Applies the tests under review in each chapter to the same purchasing card data from a government entity Includes interesting cases studies throughout that are linked to the tests being reviewed. Includes two comprehensive case studies where data analytics could have detected the frauds before they reached multi-million-dollar levels Includes a continually-updated companion website with the data sets used in the chapters, the queries used in the chapters, extra coverage of some topics or cases, end of chapter questions, and end of chapter cases. Written by a prominent educator and researcher in forensic accounting and auditing, the new edition of Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations is an essential resource for forensic accountants, auditors, comptrollers, fraud investigators, and graduate students. |
| data analysis for accountants: Accounting Information Systems Arline A. Savage, Danielle Brannock, Alicja Foksinska, 2024-01-08 |
| data analysis for accountants: Analytics and Big Data for Accountants Jim Lindell, 2018-04-11 Analytics is the new force driving business. Tools have been created to measure program impacts and ROI, visualize data and business processes, and uncover the relationship between key performance indicators, many using the unprecedented amount of data now flowing into organizations. Featuring updated examples and surveys, this dynamic book covers leading-edge topics in analytics and finance. It is packed with useful tips and practical guidance you can apply immediately. This book prepares accountants to: Deal with major trends in predictive analytics, optimization, correlation of metrics, and big data. Interpret and manage new trends in analytics techniques affecting your organization. Use new tools for data analytics. Critically interpret analytics reports and advise decision makers. |
| data analysis for accountants: Benford's Law Mark J. Nigrini, 2012-03-09 A powerful new tool for all forensic accountants, or anyone whoanalyzes data that may have been altered Benford's Law gives the expected patterns of the digits in thenumbers in tabulated data such as town and city populations orMadoff's fictitious portfolio returns. Those digits, in unaltereddata, will not occur in equal proportions; there is a large biastowards the lower digits, so much so that nearly one-half of allnumbers are expected to start with the digits 1 or 2. Thesepatterns were originally discovered by physicist Frank Benford inthe early 1930s, and have since been found to apply to alltabulated data. Mark J. Nigrini has been a pioneer in applyingBenford's Law to auditing and forensic accounting, even before hisgroundbreaking 1999 Journal of Accountancy article introducing thisuseful tool to the accounting world. In Benford's Law, Nigrinishows the widespread applicability of Benford's Law and itspractical uses to detect fraud, errors, and other anomalies. Explores primary, associated, and advanced tests, all describedwith data sets that include corporate payments data and electiondata Includes ten fraud detection studies, including vendor fraud,payroll fraud, due diligence when purchasing a business, and taxevasion Covers financial statement fraud, with data from Enron, AIG,and companies that were the target of hedge fund short sales Looks at how to detect Ponzi schemes, including data on Madoff,Waxenberg, and more Examines many other applications, from the Clinton tax returnsand the charitable gifts of Lehman Brothers to tax evasion andnumber invention Benford's Law has 250 figures and uses 50 interestingauthentic and fraudulent real-world data sets to explain boththeory and practice, and concludes with an agenda and directionsfor future research. The companion website adds additionalinformation and resources. |
| data analysis for accountants: Analytics and Big Data for Accountants Jim Lindell, 2020-12-03 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 |
| data analysis for accountants: Guide to Audit Data Analytics AICPA, 2018-02-21 Designed to facilitate the use of audit data analytics (ADAs) in the financial statement audit, this title was developed by leading experts across the profession and academia. The guide defines audit data analytics as “the science and art of discovering and analyzing patterns, identifying anomalies, and extracting other useful information in data underlying or related to the subject matter of an audit through analysis, modeling, and visualization for planning or performing the audit.” Simply put, ADAs can be used to perform a variety of procedures to gather audit evidence. Each chapter focuses on an audit area and includes step-by-step guidance illustrating how ADAs can be used throughout the financial statement audit. Suggested considerations for assessing the reliability of data are also included in a separate appendix. |
| data analysis for accountants: Data Sleuth Leah Wietholter, 2022-04-19 Straightforward, practical guidance for working fraud examiners and forensic accountants In Data Sleuth: Using Data in Forensic Accounting Engagements and Fraud Investigations, certified fraud examiner, former FBI support employee, private investigator, and certified public accountant Leah Wietholter delivers a step-by-step guide to financial investigation that can be applied to almost any forensic accounting use-case. The book emphasizes the use of best evidence as you work through problem-solving data analysis techniques that address the common challenge of imperfect and incomplete information. The accomplished author bridges the gap between modern fraud investigation theory and practical applications and processes necessary for working practitioners. She also provides: Access to a complimentary website with supplementary resources, including a Fraud Detection Worksheet and case planning template Strategies for systematically applying the Data Sleuth® framework to streamline and grow your practice Methods and techniques to improve the quality of your work product Data Sleuth is an indispensable, hands-on resource for practicing and aspiring fraud examiners and investigators, accountants, and auditors. It’s a one-of-a-kind book that puts a practical blueprint to effective financial investigation in the palm of your hand. |
| data analysis for accountants: Customer Accounting Massimiliano Bonacchi, Paolo Perego, 2018-11-04 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. |
| data analysis for accountants: Data Analytics Warren W. Stippich, 2016 |
| data analysis for accountants: Introduction to Business Lawrence J. Gitman, Carl McDaniel, Amit Shah, Monique Reece, Linda Koffel, Bethann Talsma, James C. Hyatt, 2024-09-16 Introduction to Business covers the scope and sequence of most introductory business courses. The book provides detailed explanations in the context of core themes such as customer satisfaction, ethics, entrepreneurship, global business, and managing change. Introduction to Business includes hundreds of current business examples from a range of industries and geographic locations, which feature a variety of individuals. The outcome is a balanced approach to the theory and application of business concepts, with attention to the knowledge and skills necessary for student success in this course and beyond. This is an adaptation of Introduction to Business by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License. |
| data analysis for accountants: Financial Accounting Paul D. Kimmel, Paul D Kimmel, PhD, CPA, Jerry J Weygandt, Ph.D., CPA, Donald E Kieso, Ph.D., CPA, Jerry J. Weygandt, Donald E. Kieso, 2009-08-17 |
| data analysis for accountants: Self-Service Data Analytics and Governance for Managers Nathan E. Myers, Gregory Kogan, 2021-06-02 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. |
| data analysis for accountants: Artificial Intelligence in Accounting Cory Ng, John Alarcon, 2020-12-08 Artificial Intelligence in Accounting: Practical Applications was written with a simple goal: to provide accountants with a foundational understanding of AI and its many business and accounting applications. It is meant to serve as a guide for identifying opportunities to implement AI initiatives to increase productivity and profitability. This book will help you answer questions about what AI is and how it is used in the accounting profession today. Offering practical guidance that you can leverage for your organization, this book provides an overview of essential AI concepts and technologies that accountants should know, such as machine learning, deep learning, and natural language processing. It also describes accounting-specific applications of robotic process automation and text mining. Illustrated with case studies and interviews with representatives from global professional services firms, this concise volume makes a significant contribution to examining the intersection of AI and the accounting profession. This innovative book also explores the challenges and ethical considerations of AI. It will be of great interest to accounting practitioners, researchers, educators, and students. |
| data analysis for accountants: Research Methods in Accounting Malcolm Smith, 2003-05-27 Providing a clear and concise overview of the conduct of applied research studies in accounting, Malcolm Smith presents the principal building blocks of how to implement research in accounting and related fields. |
| data analysis for accountants: The Data Revolution Rob Kitchin, 2014-09-16 Carefully distinguishing between big data and open data, and exploring various data infrastructures, Kitchin vividly illustrates how the data landscape is rapidly changing and calls for a revolution in how we think about data. - Evelyn Ruppert, Goldsmiths, University of London Deconstructs the hype around the ‘data revolution’ to carefully guide us through the histories and the futures of ‘big data.’ The book skilfully engages with debates from across the humanities, social sciences, and sciences in order to produce a critical account of how data are enmeshed into enormous social, economic, and political changes that are taking place. - Mark Graham, University of Oxford Traditionally, data has been a scarce commodity which, given its value, has been either jealously guarded or expensively traded. In recent years, technological developments and political lobbying have turned this position on its head. Data now flow as a deep and wide torrent, are low in cost and supported by robust infrastructures, and are increasingly open and accessible. A data revolution is underway, one that is already reshaping how knowledge is produced, business conducted, and governance enacted, as well as raising many questions concerning surveillance, privacy, security, profiling, social sorting, and intellectual property rights. In contrast to the hype and hubris of much media and business coverage, The Data Revolution provides a synoptic and critical analysis of the emerging data landscape. Accessible in style, the book provides: A synoptic overview of big data, open data and data infrastructures An introduction to thinking conceptually about data, data infrastructures, data analytics and data markets Acritical discussion of the technical shortcomings and the social, political and ethical consequences of the data revolution An analysis of the implications of the data revolution to academic, business and government practices |
| data analysis for accountants: Artificial Intelligence in Accounting and Auditing Mariarita Pierotti, |
| data analysis for accountants: Continuous Auditing David Y. Chan, Victoria Chiu, Miklos A. Vasarhelyi, 2018-03-21 Continuous Auditing provides academics and practitioners with a compilation of select continuous auditing design science research, and it provides readers with an understanding of the underlying theoretical concepts of a continuous audit, ideas on how continuous audit can be applied in practice, and what has and has not worked in research. |
| data analysis for accountants: Data and Analytics in Accounting Ann C. Dzuranin, Guido Geerts, Margarita Lenk, 2023-12-25 |
| data analysis for accountants: Financial Statement Analysis Martin S. Fridson, Fernando Alvarez, 2002-10-01 Praise for Financial Statement Analysis A Practitioner's Guide Third Edition This is an illuminating and insightful tour of financial statements, how they can be used to inform, how they can be used to mislead, and how they can be used to analyze the financial health of a company. -Professor Jay O. Light Harvard Business School Financial Statement Analysis should be required reading for anyone who puts a dime to work in the securities markets or recommends that others do the same. -Jack L. Rivkin Executive Vice President (retired) Citigroup Investments Fridson and Alvarez provide a valuable practical guide for understanding, interpreting, and critically assessing financial reports put out by firms. Their discussion of profits-'quality of earnings'-is particularly insightful given the recent spate of reporting problems encountered by firms. I highly recommend their book to anyone interested in getting behind the numbers as a means of predicting future profits and stock prices. -Paul Brown Chair-Department of Accounting Leonard N. Stern School of Business, NYU Let this book assist in financial awareness and transparency and higher standards of reporting, and accountability to all stakeholders. -Patricia A. Small Treasurer Emeritus, University of California Partner, KCM Investment Advisors This book is a polished gem covering the analysis of financial statements. It is thorough, skeptical and extremely practical in its review. -Daniel J. Fuss Vice Chairman Loomis, Sayles & Company, LP |
| data analysis for accountants: Auditing Raymond N. Johnson, Laura Davis Wiley, Robyn Moroney, Fiona Campbell, Jane Hamilton, 2019-05-20 The explosion of data analytics in the auditing profession demands a different kind of auditor. Auditing: A Practical Approach with Data Analytics prepares students for the rapidly changing demands of the auditing profession by meeting the data-driven requirements of today's workforce. Because no two audits are alike, this course uses a practical, case-based approach to help students develop professional judgement, think critically about the auditing process, and develop the decision-making skills necessary to perform a real-world audit. To further prepare students for the profession, this course integrates seamless exam review for successful completion of the CPA Exam. |
| data analysis for accountants: Data Science for Business Foster Provost, Tom Fawcett, 2013-07-27 Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the data-analytic thinking necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates |
| data analysis for accountants: Practitioner's Guide to Global Investigations Judith Seddon, 2018-01-19 There's never been a greater likelihood a company and its key people will become embroiled in a cross-border investigation. But emerging unscarred is a challenge. Local laws and procedures on corporate offences differ extensively - and can be contradictory. To extricate oneself with minimal cost requires a nuanced ability to blend understanding of the local law with the wider dimension and, in particular, to understand where the different countries showing an interest will differ in approach, expectations or conclusions. Against this backdrop, GIR has published the second edition of The Practitioner's Guide to Global Investigation. The book is divided into two parts with chapters written exclusively by leading names in the field. Using US and UK practice and procedure, Part I tracks the development of a serious allegation (whether originating inside or outside a company) - looking at the key risks that arise and the challenges it poses, along with the opportunities for its resolution. It offers expert insight into fact-gathering (including document preservation and collection, witness interviews); structuring the investigation (the complexities of cross-border privilege issues); and strategising effectively to resolve cross-border probes and manage corporate reputation.Part II features detailed comparable surveys of the relevant law and practice in jurisdictions that build on many of the vital issues pinpointed in Part I. |
| data analysis for accountants: Principles of Accounting Volume 1 - Financial Accounting Mitchell Franklin, Patty Graybeal, Dixon Cooper, 2019-04-11 The text and images in this book are in grayscale. A hardback color version is available. Search for ISBN 9781680922929. Principles of Accounting is designed to meet the scope and sequence requirements of a two-semester accounting course that covers the fundamentals of financial and managerial accounting. This book is specifically designed to appeal to both accounting and non-accounting majors, exposing students to the core concepts of accounting in familiar ways to build a strong foundation that can be applied across business fields. Each chapter opens with a relatable real-life scenario for today's college student. Thoughtfully designed examples are presented throughout each chapter, allowing students to build on emerging accounting knowledge. Concepts are further reinforced through applicable connections to more detailed business processes. Students are immersed in the why as well as the how aspects of accounting in order to reinforce concepts and promote comprehension over rote memorization. |
| data analysis for accountants: A Practitioner's Guide to Business Analytics (PB) Randy Bartlett, 2013-01-25 Gain the competitive edge with the smart use of business analytics In today’s volatile business environment, the strategic use of business analytics is more important than ever. A Practitioners Guide to Business Analytics helps you get the organizational commitment you need to get business analytics up and running in your company. It provides solutions for meeting the strategic challenges of applying analytics, such as: Integrating analytics into decision making, corporate culture, and business strategy Leading and organizing analytics within the corporation Applying statistical qualifications, statistical diagnostics, and statistical review Providing effective building blocks to support analytics—statistical software, data collection, and data management Randy Bartlett, Ph.D., is Chief Statistical Officer of the consulting company Blue Sigma Analytics. He currently works with Infosys, where he has helped build their new Business Analytics practice. |
| data analysis for accountants: Data Quality Jack E. Olson, 2003-01-09 Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.* Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes. * Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy. * Is written by one of the original developers of data profiling technology. * Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets. |
| data analysis for accountants: Data Scientist Zacharias Voulgaris, 2014 Learn what a data scientist is and how to become one. As our society transforms into a data-driven one, the role of the Data Scientist is becoming more and more important. If you want to be on the leading edge of what is sure to become a major profession in the not-too-distant future, this book can show you how. Each chapter is filled with practical information that will help you reap the fruits of big data and become a successful Data Scientist: Learn what big data is and how it differs from traditional data through its main characteristics: volume, variety, velocity, and veracity. Explore the different types of Data Scientists and the skillset each one has. Dig into what the role of the Data Scientist requires in terms of the relevant mindset, technical skills, experience, and how the Data Scientist connects with other people. Be a Data Scientist for a day, examining the problems you may encounter and how you tackle them, what programs you use, and how you expand your knowledge and know-how. See how you can become a Data Scientist, based on where you are starting from: a programming, machine learning, or data-related background. Follow step-by-step through the process of landing a Data Scientist job: where you need to look, how you would present yourself to a potential employer, and what it takes to follow a freelancer path. Read the case studies of experienced, senior-level Data Scientists, in an attempt to get a better perspective of what this role is, in practice. At the end of the book, there is a glossary of the most important terms that have been introduced, as well as three appendices - a list of useful sites, some relevant articles on the web, and a list of offline resources for further reading. |
| data analysis for accountants: Strategic Cost Transformation Reginald Tomas Lee, 2018-12-06 Strategic Cost Transformation offers a new framework, business domain management, which creates a comprehensive picture of your organization for improved cash based decision-making. Your product costs $2.86 to make. What does the number tell you about your operations, how effectively they were run, demand, or how much money you spent on capacity? Nothing. Shouldn’t you know? Accounting information creates a limited picture of operations and true cash performance. Strategic Cost Transformation offers a new framework, business domain management, which creates a comprehensive picture of your organization for improved cash based decision-making. |
| data analysis for accountants: Data Analytics for Accounting Vernon J. Richardson, Ryan Teeter, Katie Terrell, 2019 |
| data analysis for accountants: The Essentials of Machine Learning in Finance and Accounting Mohammad Zoynul Abedin, M. Kabir Hassan, Petr Hajek, Mohammed Mohi Uddin, 2021-06-20 This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data. Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management. |
| data analysis for accountants: Applied Predictive Modeling Max Kuhn, Kjell Johnson, 2013-05-17 Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. |
| data analysis for accountants: Financial and Managerial Accounting Jerry J. Weygandt, Paul D. Kimmel, Donald E. Kieso, 2011-12-19 Financial and Managerial Accounting, by Weygandt, Kimmel, Kieso is a new introductory program for the two semester accounting sequence that presents equal coverage of both introductory financial and managerial accounting topics. The Team for Success authors of Jerry Weygandt, Paul Kimmel, and Don Kieso bring years of industry, academic, and writing experience to the development of this new title which gives students the tools they need to understand the accounting cycle and key financial accounting topics, while presenting the managerial topics in an easy-to-understand fashion in a decision-making framework. The Team for Success authors understand where students struggle in introductory accounting, and have developed a learning system that illustrates the accounting cycle and key transactions, while giving student the tools to apply their learning through sample exercises throughout the chapter. Weygandt Financial and Managerial Accounting relates accounting concepts to real-world experiences, is full relevant examples to students' lives, and provides IFRS coverage that will prepare students for the global economy. Students using Weygandt, Financial and Managerial Accounting with WileyPLUS will spend more time with the material because it demonstrates the relevance and offers multiple opportunities for practice both in the book and in WileyPLUS. Students take more initiative with their learning, so you'll have a greater impact in the classroom. WileyPLUS sold separately from text. |
| data analysis for accountants: Managerial Accounting Jerry J. Weygandt, Ibrahim M. Aly, Donald E. Kieso, Paul D. Kimmel, 2011-10-31 |
| data analysis for accountants: Public Policies and the Industrial Economy of India Since Independence Kalipada Deb, 1987 |
| data analysis for accountants: Accounting Information Systems Chengyee Janie Chang, Vernon Richardson, Professor, Rod E. Smith, Professor, 2013-09-03 Accounting Information Systems 1e covers the four roles for accountants with respect to information technology: 1. Users of technology and information systems, 2. Managers of users of technology, 3. Designers of information systems, and 4. Evaluators of information systems. Accountants must understand the organisation and how organisational processes generate information important to management. Richardson's focus is on the accountant's role as business analyst in solving business problems by database modeling, database design, and business process modeling. Unlike other texts that provide a broad survey of AIS related topics, this text concentrates on developing practical, real-world business analysis skills. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data Analytics Knowledge Required of CPA: A Normative …
data-centric business environment, acquiring the knowledge and skills of data analysis should be a current professional priority. Keywords: Audit Data Analytics, Knowledge, Skill, Accounting …
FORENSIC ACCOUNTING AND FRAUD DETECTION: A REVIEW …
Forensic accountants scrutinize balance sheets, income statements, and cash flow statements to identify anomalies, discrepancies, or irregular patterns that may indicate financial …
AI (ARTIFICIAL INTELLIGENCE) IN THE FINANCE PROFESSION
with financial planning and analysis (regressions / logistic regressions, decision trees for forecasting, analysing impact of variable changes, scenario planning), audit (anomaly …
ANALYSIS OF TECHNOLOGY READINESS OF GENERATION Z …
Revolution, AI plays an increasingly vital role in data analysis, decision-making, and business strategy development for accountants. Research conducted by (Anh et
Big data and decision quality: The role of management …
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The impact of AI on accounting practices: A review: Exploring …
Accountants must now possess a blend of traditional accounting knowledge and technological proficiency. Understanding and leveraging AI tools has become integral to the modern …
5th Edition Financial And Managerial Accounting
identifying areas where data analysis can improve decision-making. Explore available tools and resources, and seek out opportunities to participate in data analysis projects. 3. What are the …
Can Robots Replace Accountants? The Impact of Information …
Management accountants perceive automation positively, viewing it as an opportunity for professional growth and improved task efficiency [23]. The shift towards automation requires …
Accountants’ perception of AI and their - UTUPub
Accountants’ perception of AI and their willingness to utilize it Information Systems Science Turku School of Economics / TiSeM Master's thesis ... data analysis. Although AI could bring a lot to …
A STUDY ON THE RELATIONSHIP BETWEEN BURNOUT AND …
completely by 159 teachers, who work at universities and schools in Iran. After data analysis, the findings showed a negative correlation between teachers’ burnout and their job satisfaction; …
Forensic Accounting, a Tool for Detecting and Preventing the …
Tools and Methodologies of Financial Analysis within forensic accounting involve using specialized financial analysis software, which allows for detailed examination of transactions …
The Institute of Chartered Accountants of Nigeria (ICAN)
data from various accounting systems, extracting relevant information, and presenting it in a structured and organized format for financial statement . preparation. 2. Data Analysis: GenAI …
Ethical Dilemmas in Accounting: A Comprehensive Analysis of ...
Compliance" is the most prioritized area with 70 accountants, followed by "Upholding Public Trust" (60 accountants), "Credibility of Financial Information" (50 accountants), "Long-Term Success …
Roles of Accountants and Sustainable Development Goals in …
The data analysis technique used is by reviewing and describing the SDGs, which are the priority of each palm oil company in Indonesia with the content analysis method, then integrated with …
The Uses of Critical Thinking in Accounting and How It …
So, firstly, it is critical that accountants produce useful quantitative information for internal and external users in data analysis and decision making. Also, accounting is not a static but a …
Excel for Accountants - New View Strategies
Excel for Accountants As former accountants we know how important Excel is to your transaction processing, research, and analysis, each and every day. We also know that no-one has the …
Exploring the Importance of Soft Skills Training for …
postings triangulated the semistructured interviews. Data analysis entailed coding, conceptualizing concepts and ideas, identifying themes, and member checking to ensure the …
Adoption of Big Data analytics tools by accountants …
demand is to the detriment of accountants (WEF Future of Jobs 2020; Schmidt and Riley, 2020). Big data (BD) is described as hefty data volumes that may be structured and/or unstructured …
University of Arkansas, - etextbook.to
data dictionary for a larger database (data dictionaries can be upward of 100 pages long), even in this example, having some background knowledge on primary and foreign keys is critical. …
FINAL LEVEL CHAPTER 16(UNIT-3) FORENSIC AUDIT
Ratio Analysis: Another useful fraud detection technique is the calculation of data analysis ratios for key numeric fields. Like financial ratios that give indications of the financial health of a …
A Preliminary Investigation of the Necessary Skills, Education ...
35 • Computer forensics skills - Today, almost every fraud involves the use of computers and digital documents (Smith, 2005). • Data mining skills – Data mining, which uses mathematical …
Accountant as Digital Innovator: Roles and Competencies in …
Our analysis reveals that accountants play important roles as identifiers, explainers, trainers, sustainers, and analyzers of their organizations’ automation initiatives.
Big data and analytics – what’s new?
generates new data about the location of individuals. • Open data refers to the release of large amounts of primarily public sector data, such as geo-spatial data, transport data, government …
Original Contribution The Integration of Artificial Intelligence …
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New technology and desired skills of early career accountants
to using data generated by technology to inform stakeholder strategies, resulting in changing ... Accountants, especially ECAs, are now expected to have the expertise and skills to ...
The Complete Guide Document Scanning For Accountants
retrieval to data analysis, saving time that can then be channeled into more valuable, client-focused work. Simplify Compliance With digital records, automated tagging and archival …
The Effect of MBKM Mandiri Internship Program, Career
The data analysis technique used is multiple linear regression. This study found that the MBKM Mandiri internship program and career motivation have a positive ... public accountants in …
Sectoral Risk Assessment of Accountants in Nigeria - scuml.org
Mar 1, 2025 · contributions of the staff of the NFIU, whose technical expertise, research, and data analysis played a pivotal role in this exercise, are deeply acknowledged. Special recognition …
Forensic Accounting and Financial Fraud in Nigeria: Problems …
employed in the data analysis. The tests of hypothesis were done using Microsoft Excel 2010 version. Tests were carried out at a significant level of 5% and three degree of ... conduct …
What is Production Accounting? - CAPPA
What is Production Accounting? We strongly rely on the other asset management disciplines and the field to effectively perform our duties. Data used in our day-to-day job functions is relayed …
Finance Curriculum vs. Accounting Curriculum: How Are They …
Thanks to new technologies that automate processes and enable deep analysis, both the finance and the accounting curricula may also emphasize technical and data analysis skills. But …
A Study on Financial Performance Analysis with Reference to …
section the primary data were collected. The annual report and manuals for financial performance form the basis for secondary data collection. The compilation, edition and tabulation of the …
Menguasai Perubahan, Menyiapkan Masa Depan! IKATAN …
Big data arid data analytics Sources of data Types of analytics Data analytics-methodologies Mainstream tools and key applications of data analytics Practice and Mock-exam Course …
Forensic Focus - KPMG
Forensic accountants arm lawyers with valuable insights Forensic accountants with significant AB&C experience have developed sophisticated AB&C data analytic tools that add …
Data Analytics for Accountants and Auditors - 2020 Innovation
analysis Data Analytics: Analyzing raw data to make conclusions about that information. Can be used for understanding and/or decision making Database: A place where data is stored in a …
A STUDY OF BURNOUT IN CERTIFIED PUBLIC ACCOUNTANTS
exam. These staff accountants are faced with the demands of the workplace while studying for the CPA exam, which has also had new content added (Carpenter & Hook, 2008). This has had a …
MS-EXCEL FOR CHARTERED ACCOUNTANTS - sbgco.co.in
1 Basics & Beyond.. 1.1 Introduction Microsoft Excel is a spreadsheet program that is designed to record and analyze numbers and data. Excel is very widely used for accounting and financial …
Accountants’ Perceptions of the Use of Excel ... - ResearchGate
Accountants’ Perceptions of the Use of Excel ... to gather primary data- the Pearson Moment Correlation co-efficient, Z-statistics and simple statistical tools for analysis. The first hypothesis
Journal of Forensic and Investigative Accounting Personal
data analysis that provides an accessible, comprehensive, and flexible approach for transcript analysis (Braun and Clarke, 2006; Nowell et al., 2017). Attard and Coulson reported that …
DAAB A4.cdr - Institute of Chartered Accountants of India
• Data Analysis for Auditors (Practical Case Studies on Using CAAT's) ... ICAI Course on Blockchain Technology for Professional Accountants Forensic Labs (Data Analytics Labs) of …
Business Analytics: Transforming the Role of Management …
MANAGEMENT ACCOUNTING QUARTERLY 4 SPRING 2015, VOL. 16, NO. 3 data with their internal data for richer analysis and in - sight. Research company Gartner predicts that the …
Forensic Accounting and Fraud Detection Emerging Trends …
effectiveness, and trustworthiness of fraud detection processes through a thorough analysis. The article will investigate how these technologies are used in real-world situations by analyzing …
THE IMPACT OF DIGITAL TRANSFORMATION ON FINANCIAL …
324 Volume: 8 Issues: 50 [September, 2023] pp. 324 - 336 International Journal of Accounting, Finance and Business (IJAFB) eISSN: 0128-1844 Journal website: www.ijafb.com
Exploring the Importance of Soft Skills Training for …
postings triangulated the semistructured interviews. Data analysis entailed coding, conceptualizing concepts and ideas, identifying themes, and member checking to ensure the …
Course Title: AI for Chartered Accountants (AICA)-Level 1
Tools and techniques for data analysis in Finance & Audit. Case studies on data-driven decision-making. Hands-on exercise with a popular Dx for Accounting tool. AI Use Cases for Members …
Transformation of Artificial Intelligence in the Accounting …
accountants by AI systems, challenges to data privacy and security, and ethical issues that arise. The roles and responsibilities of accountants have also changed. Accountants need to …
TECHNOLOGICAL DISRUPTION IN ACCOUNTING: REGTECH, …
AI also bolsters data analysis and reporting capabilities within RegTech. With advancements in AI algorithms, it is now feasible to process vast volumes of structured and unstructured data in …
Course Title: AI for Chartered Accountants (AICA)-Level 1
Tools and techniques for data analysis in Finance & Audit. Case studies on datadriven decision-making. Hands-on exercise with a popular Dx for Accounting tool. AI Use Cases for Members …
