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| data science for accountants: Data Analytics for Accounting Vernon J. Richardson, Ryan Teeter, Katie L. Terrell, 2018-05-23 |
| data science 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 science for accountants: Fourth Industrial Revolution and Business Dynamics Nasser Rashad Al Mawali, Anis Moosa Al Lawati, Ananda S, 2021-10-07 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 science for accountants: Data Science Field Cady, 2020-12-30 Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary – A Technical Book for Non-Technical Professionals is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the “business side” of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. Data Science: The Executive Summary covers topics like: Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts’ hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation. |
| data science 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 science for accountants: Accounting Information Systems Arline A. Savage, Danielle Brannock, Alicja Foksinska, 2024-01-08 |
| data science 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 science 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 science 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 science 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 science for accountants: Digital Transformation in Accounting Richard Busulwa, Nina Evans, 2021-05-30 Digital Transformation in Accounting is a critical guidebook for accountancy and digital business students and practitioners to navigate the effects of digital technology advancements, digital disruption, and digital transformation on the accounting profession. Drawing on the latest research, this book: Unpacks dozens of digital technology advancements, explaining what they are and how they could be used to improve accounting practice. Discusses the impact of digital disruption and digital transformation on different accounting functions, roles, and activities. Integrates traditional accounting information systems concepts and contemporary digital business and digital transformation concepts. Includes a rich array of real-world case studies, simulated problems, quizzes, group and individual exercises, as well as supplementary electronic resources. Provides a framework and a set of tools to prepare the future accounting workforce for the era of digital disruption. This book is an invaluable resource for students on accounting, accounting information systems, and digital business courses, as well as for accountants, accounting educators, and accreditation / advocacy bodies. |
| data science 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 science for accountants: Handbook of Big Data and Analytics in Accounting and Auditing Tarek Rana, Jan Svanberg, Peter Öhman, Alan Lowe, 2023-02-03 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. |
| data science 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 science for accountants: Handbook of Research on Accounting and Financial Studies Farinha, Luís, Cruz, Ana Baltazar, Sebastião, João Renato, 2020-03-06 The competitive nature of organizations in today’s globalized world has led to the development of various approaches to increasing profitability and maintaining an advantage over rival companies. As technology continues to be integrated into business practices, specifically in the area of accounting and finance, professionals and educators need to be prepared for advancing economic techniques, and they need to maintain a high level of financial literacy. The Handbook of Research on Accounting and Financial Studies is a pivotal reference source that provides vital research on advanced knowledge and emerging business practices and teaching dynamics in the fields of accounting and finance. While highlighting topics such as cost-benefit analysis, risk management, and corporate governance, this publication explores new initiatives in entrepreneurship and performance management. This book is ideally designed for business managers, consultants, entrepreneurs, auditors, tax practitioners, economists, accountants, academicians, researchers, and students seeking current research on modern advancements and recent findings in accounting and financial studies. |
| data science for accountants: Career as a Forensic Accountant Institute for Career Research, 2019 |
| data science for accountants: Artificial Intelligence in Accounting and Auditing Mariarita Pierotti, |
| data science for accountants: Core Concepts of Accounting Information Systems Stephen A. Moscove, Mark G. Simkin, Nancy A. Bagranoff, 1997 This book is entirely up to date to reflect recent changes in technology and AIS practive. Covers such subjects as EDI, reengineering, neural networks, client/server, computer security, and events accounting. |
| data science for accountants: Python for Finance Yves J. Hilpisch, 2018-12-05 The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks. |
| data science 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 science 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 science 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 science for accountants: Modeling and Designing Accounting Systems: Using Access to Build a Database JANIE C. CHANG, 2012 |
| data science for accountants: Data Analytics Warren W. Stippich, 2016 |
| data science 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 science for accountants: Deep Finance Glenn Hopper, 2021-11-16 Deep Finance is informative, enlightening, and embraces the innovation all around us - perfect for trailblazing CFOs ready to dive deep into an era of information, analytics, and Big Data. ARE YOU READY FOR A DIGITAL TRANSFORMATION? LEAD THE AGE OF ANALYTICS WITH DEEP FINANCE. Glenn Hopper uses a unique blend of financial leadership and technical expertise to help businesses of all sizes optimize and modernize. Not a software engineer? Neither is Glenn Hopper, but his story shows how any finance leader can embrace the tech innovations shaping our world to revolutionize finance operations. Accounting has come a long way since the time of the abacus, computer punch cards, or even the paper ledger. Modern finance leaders have the ability and tools to build a team that harnesses the power of business intelligence to make their jobs easier. Leaders who aren’t aware of these opportunities are simply going to be outpaced by competitors willing to adapt to the 21st century and beyond. Deep Finance will take you from asking “What Is AI?” to walking a clear path toward your own digital transformation. Elevate your leadership and be a champion for data science in your department. In Deep Finance, you will: · Study the history of accounting—and why the age of analytics is the next logical step for all finance departments. · Step into the age of artificial intelligence and view the pathway to a digital transformation. · Expand your role as CFO by integrating business intelligence and analytics into your everyday tasks. · Weigh the pros and cons of buying or building software to manage transactions, analyze and collect data, and identify trends. · Become a “New Age CFO” who can make better financial decisions and identify where your company is moving. · Develop the language to elevate your entire management team as you enter the age of artificial intelligence. Don’t get left behind. Your competitors or team members recognize the possibilities that are available to finance departments everywhere. Take the first steps toward a digital transformation and evolution to a data-driven culture. Grab your copy of Deep Finance today! |
| data science for accountants: Fundamentals of Forensic Accounting Certificate Program AICPA, 2019-04-09 The Fundamentals of Forensic Accounting Certificate Program (21.5 CPE credits) covers those areas representative of the AICPA's Body of Knowledge in the financial forensics area. This certificate program is tailored to provide an introduction to financial forensics and help you become familiar with the forensic accountant's professional responsibility. It provides a foundational knowledge of: The legal system How to plan and prepare a forensic engagement Gathering information Discovery Reporting Providing expert testimony This online CPE self-study certificate program consists of 19 required modules that utilize interactive scenario-based learning, including audio and video animation, to guide you through the concepts, including: AICPA Guidance for the Forensic Engagement Understanding the Forensic Accountant Role Understanding the Basic Structure of the Legal System Managing the Forensic Engagement Identifying and Obtaining Evidence Conducting Effective Interviews Common Investigative Techniques Deposition and Testimony Reporting Requirements & Preparing Sustainable Reports Bankruptcy, Insolvency and Reorganization Leveraging Technology in Forensic Engagements Economic Damages in Business Economic Damages for Individuals: A CPA's Role Economic Damages for Individuals: Case Studies and Analysis Calculating Intellectual Property Infringement Damages Family Law Engagements Fraud Prevention, Detection, and Response Financial Statement Fraud and Asset Misappropriation Valuations in Litigation Matters Key Topics Bankruptcy, Insolvency and Reorganization Computer Forensic Analysis Economic Damages Calculations Family Law Financial Statement Misrepresentation Fraud Prevention, Detection and Response Valuation Learning Objectives Interpret regulatory standards and legal system requirements applicable to forensic accounting engagements Describe the elements essential to accepting forensic accounting engagements such as identifying the engagement terms and client provisions, managing the engagement, and reporting requirements Identify the means of gathering evidence and conducting research critical to forensic engagements through the use of effective interviewing and investigative techniques Describe the role of the expert and non-expert in participating in depositions and providing testimony Credit Info CPE CREDITS: Online: 21.5 (CPE credit info) NASBA FIELD OF STUDY: Accounting LEVEL: Basic PREREQUISITES: None ADVANCE PREPARATION: None DELIVERY METHOD: QAS Self-Study COURSE ACRONYM: FACERTBundle.EL Online Access Instructions A personal pin code is enclosed in the physical packaging that may be activated online upon receipt. Once activated, you will gain immediate online access to the product. System Requirements AICPA’s online CPE courses will operate in a variety of configurations, but only the configuration described below is supported by AICPA technicians. A stable and continuous internet connection is required. In order to record your completion of the online learning courses, please ensure you are connected to the internet at all times while taking the course. It is your responsibility to validate that CPE certificate(s) are available within your account after successfully completing the course and/or exam. Supported Operating Systems: Macintosh OS X 10.10 to present Windows 7 to present Supported Browsers: Apple Safari Google Chrome Microsoft Internet Explorer Mozilla Firefox Required Browser Plug-ins: Adobe Flash Adobe Acrobat Reader Technical Support: Please contact service@aicpa.org. Frequently Asked Questions What is the Fundamentals of Forensic Accounting Certificate Program? Developed by the AICPA, this certificate program is specially designed to help accountants and others 1) build the knowledge needed to gain a basic understanding of the field of forensic accounting, 2) earn CPE credits needed to meet the 75-hour education requirement for the Certified in Financial Forensics (CFF) credential, or 3) earn CPE credits needed to maintain the CFF credential. Why should I participate? Certificate holders will learn or be refreshed on the core material in professional standards that applies to forensic engagements. The program provides participants with a solid understanding of how to work within the court system when engaged as a forensic accountant. With information provided by subject matter experts from each of the specialization areas, participants are provided first-hand knowledge that guides them through solid investigation, documentation, reporting and other required skills. A series of 20 courses takes you through the best practices styles for performing an engagement. These knowledge and skills are necessary for an accountant and others who are considering entering or are already in the field of forensic accounting. Is the certificate program available to both CPAs and other accounting professionals who are not CPAs? Yes. The courses that comprise the Fundamentals of Forensic Accounting Certificate Program curriculum are available for CPAs, CAs and other accounting professionals who do not have one of these credentials or their equivalent. What level of knowledge should I possess prior to starting the certificate program? All individuals pursuing the Forensic Accounting Certificate of Achievement should possess a base knowledge of AICPA Auditing Standards. What course topics are included in the curriculum? The certificate program includes 19 required modules, including: 3 Fundamental modules, 6 Forensic Engagement modules, and 10 Specialized Knowledge modules. In total, the program provides 21.5 CPE hours at a basic level. Visit AICPAStore.com/forensic for a list of modules included in the program. All modules will be approximately 50-minutes long and provide individual CPE credit upon successful completion of the end-of-module exam. Some modules may be longer than 50 minutes, as required by the depth or complexity of the content, with a maximum length of 2 hours. How long will it take me to complete all of courses of the Fundamentals of Forensic Accounting Certificate Program? This varies from individual to individual and is completely dependent upon the time the participant allocates to completing the coursework. There is a commitment of 21.5 required hours to successfully complete the program. What period of time do I have to complete the entire curriculum? Once you enter the program you have twenty-four (24) months from the date of purchase. You are encouraged to complete the program within a twelve (12) month period or less. Once I complete the curriculum and obtain my Forensic Accounting Certificate of Achievement, is there a time period for which it is active? No. The Forensic Accounting Certificate is not a professional credential or license. It is evidence of successful completion of a required course curriculum as of a point in time. As a result, it has no period for which it is deemed active or in-force. Am I required to obtain a certain number of CPE credits annually for the certificate to remain current and active? No. The Forensic Accounting Certificate of Achievement is not a professional credential or license. It is evidence of successful completion of a required course curriculum as of a point in time. As a result, it has no period for which it is deemed active or in-force. If I am a CPA, will I receive CPE credit toward my CPA license if I take this program? Yes, all of the courses in the Fundamentals of Forensic Accounting Certificate Program will qualify for CPE credit. The AICPA is a NASBA-approved provider of CPE. How many credits of CPE will I receive if I earn the certificate? Completing the curriculum will result in earning 21.5 credits. All of these credit hours will qualify for CPE credit and can count toward meeting your state's CPE requirements. Will the CPE credit satisfy my requirements for CMA, CIA or other certifications? The courses in the Fundamentals of Forensic Accounting Certificate Program will be classified as Accounting for purposes of granting CPE credits. As with other AICPA courses that are approved for other certifications, we fully expect the Forensic Accounting Certificate courses will satisfy those requirements. To be certain, please check with the organization that issues your CMA, CIA or other certifications. If I am unable to complete the entire Fundamentals of Forensic Accounting Certificate Program, will I receive CPE credit for the courses I do complete? Yes. The courses are offered individually, so you will earn NASBA QAS CPE credit for each course you take and successfully complete the exam. You are not required to complete the entire program to earn CPE credit. However, you must successfully complete the exam for all required courses in the entire program in order to receive the Forensic Accounting Certificate of Achievement. I have prior experience in working with forensic accounting. Will I be allowed to test out of certain courses while still earning the certificate? Actual completion of the courses is required to earn the Forensic Accounting Certificate. CPE credit will be awarded for the courses, and the CPE standards do not allow for testing out of a course as a way to earn credit. Is the entire program fixed, or are their elective courses I can select from in earning the certificate? The curriculum for the Forensic Accounting Certificate is fixed. It is designed to provide participants with a solid understanding of knowledge required to perform forensic accounting engagements. In order to receive the Forensic Accountant Certificate of Achievement all required modules must be completed. What are the systems requirements for the e-learning portion of the program? Please review the information on the System Requirements tab for this product for complete information on minimum operating system and browser requirements. I am already proficient in forensic accounting but would like to learn more about a few select topics that are specific to my job. Can I purchase individual titles in the Fundamentals of Forensic Accounting Certificate Program separately? Yes. Courses in the Certificate Program may be purchased individually. If you decide that you would like to enroll in the full Certificate Program after purchasing one or more individual courses, credit for those courses may be applied to the purchase amount of the full program as long as they have been purchased within one year of enrolling in the full program. Please call the AICPA service center at 888.777.7077 for more information. Can credits earned in the Fundamentals of Forensic Accounting Certificate Program be applied towards the 75-hour minimum CPE requirement to apply for the Certified in Financial Forensics (CFF) Credential? Yes. Courses in the Certificate Program can be applied toward the requirement to apply for the credential as well as the ongoing education requirement. When will I receive a hard copy of my certificate? You will receive your certificate in the mail 6-8 weeks after completing the program. |
| data science 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 science 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 science 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 science for accountants: Data and Analytics in Accounting Ann C. Dzuranin, Guido Geerts, Margarita Lenk, 2023-12-25 |
| data science 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 science for accountants: Big Data, Cloud Computing, Data Science & Engineering Roger Lee, 2018-08-13 This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science. |
| data science for accountants: Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics Patil, Bhushan, Vohra, Manisha, 2020-10-23 Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies. |
| data science for accountants: Microsoft Excel 2019 Data Analysis and Business Modeling Wayne Winston, 2019-03-28 Master business modeling and analysis techniques with Microsoft Excel 2019 and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. New coverage ranges from Power Query/Get & Transform to Office 365 Geography and Stock data types. Practice with more than 800 problems, many based on actual challenges faced by working analysts. Solve real business problems with Excel—and build your competitive advantage: Quickly transition from Excel basics to sophisticated analytics Use PowerQuery or Get & Transform to connect, combine, and refine data sources Leverage Office 365’s new Geography and Stock data types and six new functions Illuminate insights from geographic and temporal data with 3D Maps Summarize data with pivot tables, descriptive statistics, histograms, and Pareto charts Use Excel trend curves, multiple regression, and exponential smoothing Delve into key financial, statistical, and time functions Master all of Excel’s great charts Quickly create forecasts from historical time-based data Use Solver to optimize product mix, logistics, work schedules, and investments—and even rate sports teams Run Monte Carlo simulations on stock prices and bidding models Learn about basic probability and Bayes’ Theorem Use the Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook Automate repetitive analytics tasks by using macros |
| data science for accountants: Analytics, Data Science, and Artificial Intelligence Ramesh Sharda, Dursun Delen, Efraim Turban, 2020-03-06 For courses in decision support systems, computerized decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisionsAnalytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus -- analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT. |
| data science for accountants: Encyclopedia of Data Science and Machine Learning Wang, John, 2023-01-20 Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians. |
| data science for accountants: ChatGPT and AI for Accountants Dr. Scott Dell, Dr. Mfon Akpan, 2024-06-28 Elevate your accounting skills by applying ChatGPT across audit, tax, consulting, and beyond Key Features Leverage the impact of AI on modern accounting, from audits to corporate governance Use ChatGPT to streamline your accounting tasks with practical hands-on techniques Understand the impact of AI in accounting through in-depth chapters covering various domains, including ethical considerations and data analytics Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the fast-paced AI world, accounting professionals are increasingly challenged by the complexities of AI. Many struggle to integrate these advanced tools into their workflows, leading to a sense of overwhelm. ChatGPT for Accounting bridges this gap by not only simplifying AI concepts but also offering practical insights for its application in various accounting domains. This book takes you from the foundational principles of Generative Artificial Intelligence (GAI) to its practical applications in audits, tax planning, practice management, fraud examination, financial analysis, and beyond. Each chapter equips you with essential skills, showing you how AI can revolutionize internal control systems, enhance recruitment processes, streamline marketing plans, optimize tax strategies, and boost efficiency in audits. You’ll then advance to exploring the role of AI in forensic accounting, financial analysis, managerial accounting, and corporate governance, while also addressing ethical and security implications. Concluding with a reflective outlook on the promises and challenges of AI, you’ll gain a holistic view of the future of accounting. By the end of this book, you’ll be equipped with the knowledge to harness the power of AI effectively and ethically, transforming your accounting practice and staying ahead in the ever-evolving landscape.What you will learn Understand the fundamentals of AI and its impact on the accounting sector Grasp how AI streamlines and enhances the auditing process for high accuracy Uncover the potential of AI in simplifying tax processes and ensuring compliance Get to grips with using AI to identify discrepancies and prevent financial fraud Master the art of AI-powered data analytics for informed decision-making Gain insights into seamlessly integrating AI tools within existing accounting systems Stay ahead in the evolving landscape of AI-led accounting tools and practices Who this book is for Whether you're a seasoned accounting professional, a C-suite executive, a business owner, an accounting educator, a student of accounting, or a technology enthusiast, this book provides the knowledge and insights you need to navigate the changing landscape in applying GAI technology to make a difference in all you do. An appreciation and understanding of the accounting process and concepts will be beneficial. |
| data science 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 science for accountants: Data Analytics Arthur Zhang, 2017-03-10 The Ultimate Guide to Data Science and Analytics This practical guide is accessible for the reader who is relatively new to the field of data analytics, while still remaining robust and detailed enough to function as a helpful guide to those already experienced in the field. Data science is expanding in breadth and growing rapidly in importance as technology rapidly integrates ever deeper into business and our daily lives. The need for a succinct and informal guide to this important field has never been greater. RIGHT NOW you can get ahead of the pack! This coherent guide covers everything you need to know on the subject of data science, with numerous concrete examples, and invites the reader to dive further into this exciting field. Students from a variety of academic backgrounds, including computer science, business, engineering, statistics, anyone interested in discovering new ideas and insights derived from data can use this as a textbook. At the same time, professionals such as managers, executives, professors, analysts, doctors, developers, computer scientists, accountants, and others can use this book to make a quantum leap in their knowledge of big data in a matter of only a few hours. Learn how to understand this field and uncover actionable insights from data through analytics. UNDERSTAND the following key insights when you grab your copy today: WHY DATA IS IMPORTANT TO YOUR BUSINESS DATA SOURCES HOW DATA CAN IMPROVE YOUR BUSINESS HOW BIG DATA CREATES VALUE DEVELOPMENT OF BIG DATA CONSIDERING THE PROS AND CONS OF BIG DATA BIG DATA FOR SMALL BUSINESSES THE COST EFFECTIVENESS OF DATA ANALYTICS WHAT TO CONSIDER WHEN PREPARING FOR A NEW BIG DATA SOLUTION DATA GATHERING DATA SCRUBBING DESCRIPTIVE ANALYTICS INFERENTIAL STATISTICS PREDICTIVE ANALYTICS PREDICTIVE MODELS DESCRIPTIVE MODELING DECISION MODELING PREDICTIVE ANALYSIS METHODS MACHINE LEARNING TECHNIQUES DATA ANALYSIS WITH R ANALYTICAL CUSTOMER RELATIONSHIP MANAGEMENT (CRM) THE USE OF PREDICTIVE ANALYTICS IN HEALTHCARE THE USE OF PREDICTIVE ANALYTICS IN THE FINANCIAL SECTOR PREDICTIVE ANALYTICS & BUSINESS MARKETING STRATEGIES FRAUD DETECTION SHIPPING BUSINESS CONTROLLING RISK FACTORS THE REVOLUTION OF PREDICTIVE ANALYSIS ACROSS A VARIETY OF INDUSTRIES DESCRIPTIVE AND PREDICTIVE ANALYSIS CRUCIAL FACTORS FOR DATA ANALYSIS RESOURCES AND FLEXIBLE TECHNICAL STRUCTURE BUSINESS INTELLIGENCE HYPER TARGETING WHAT IS DATA SCIENCE? DATA MUNGING DEMYSTIFYING DATA SCIENCE SECURITY RISKS TODAY BIG DATA AND IMPACTS ON EVERYDAY LIFE FINANCE AND BIG DATA APPLYING SENTIMENT ANALYSIS RISK EVALUATION AND THE DATA SCIENTIST THE FINANCE INDUSTRY AND REAL-TIME ANALYTICS HOW BIG DATA IS BENEFICIAL TO THE CUSTOMER CUSTOMER SEGMENTATION IS GOOD FOR BUSINESS USE OF BIG DATA BENEFITS IN MARKETING GOOGLE TRENDS THE PROFILE OF A PERFECT CUSTOMER LEAD SCORING IN PREDICTIVE ANALYSIS EVALUATING THE WORTH OF LIFETIME VALUE BIG DATA ADVANTAGES AND DISADVANTAGES MAKING COMPARISONS WITH COMPETITORS DATA SCIENCE IN THE TRAVEL SECTOR SAFETY ENHANCEMENTS THANKS TO BIG DATA BIG DATA AND AGRICULTURE BIG DATA AND LAW ENFORCEMENT THE USE OF BIG DATA IN THE PUBLIC SECTOR BIG DATA AND GAMING PRESCRIPTIVE ANALYTICS GOOGLE'S SELF-DRIVING CAR AND MUCH MORE! WANT MORE? Scroll up and grab this helpful guide toady! |
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 enable a …
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 to …
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 …
