JCAATs - Data Analysis and Smart Audit (Attached：Trial version software + Dataset)

＜內容簡介＞ ◎The world's first general audit software with AI, designed to run on both Mac and Windows OS. With the advent of the Al era, professionals need to select the right tools to meet new opportunities and challenges! This instructional material focuses on the application of big data analysis, text mining, and machine learning in auditing to assist readers in understanding the latest developments in data analysis and smart audit. JCAATs is a new generation audit software developed by Python, which can be executed in a Windows and MAC operation systems with a multi-language, visual, and easy-to-use interface. Non-IT professionals can easily conduct smart data analysis. Through JCAATs' built-in data fusion technology and OPEN DATA connector, heterogeneous data can be quickly analyzed in real-time and effectively identifying anomalies. The features of this book include: ◆The book is structured to provide a progressive learning experience, with chapters covering different concepts and applications, as well as exercises and practice questions. ◆The official textbook endorsed by ICAEA for the ICCP (International Certified CAATs Practitioner) certification exams. ◆This book provides an educational version of the JCAATs - AI audit software for trial use, with a multi-language interface. The book provides several practical examples which allowing you to hands-on practice for smart auditing. This material is suitable for professionals such as accountants, auditors, compliance officers, risk managers, information security professionals, managers at all levels, and college students as a learning reference. To cultivate AI programming skills in business schools and other institutions, the International Computer Auditing Education Association (ICAEA) recommends starting with No Code. This approach allows students to develop audit applications to solve real-world problems without needing to write any code, giving them practical experience and enhancing their professional value. Once proficient in No Code, students can progress to Read Code training, where they gain an understanding of coding logic. Finally, Write Code training enables them to create their own AI applications. This approach prepares students for a future working environment centered on data analysis and smart auditing, where they can collaborate with AI auditing robots. As the AI era presents new challenges to the education of business professionals, colleges must adopt innovative and effective approaches to prepare their students for the workforce of the future. ★目錄： JCAATs - Data Analysis and Smart Audit Part 1: Text Book + Exercise + Case Studies Chapter 1 Introduction to Data Analysis and Smart Audit Chapter 2 Overview of JCAATs - AI Audit software Chapter 3 Project Chapter 4 Data Chapter 5 Expressions Chapter 6 Validation Chapter 7 Analysis Chapter 8 Script Chapter 9 Text Mining Chapter 10 Machine Learning Chapter 11 Reporting Chapter 12 Sampling Chapter 13 Tools Part 2: Exercise Solution + Practice Chapter 3 Exercise solutions for Project Chapter 4 Exercise solutions for Data Chapter 5 Exercise solutions for Expressions Chapter 6 Exercise solutions for Validation Chapter 7 Exercise solutions for Analysis Chapter 8 Exercise solutions for Script Chapter 9 Exercise solutions for Text Mining Chapter 10 Exercise solutions for Machine Learning Chapter 11 Exercise solutions for Reporting Chapter 12 Exercise solutions for Sampling Chapter 13 Exercise solutions for Tools Appendix A References Appendix B Other Learning Resources ＜作者簡介＞ Sherry Huang She is a CEO of Jacksoft Ltd. which is one of top audit technology innovative company in Asia. Sherry has more than 20 years of experience in the IT service industry, providing consultancy services to over 500 enterprises in the audit industry. She currently serves as the chair of the ICAEA Taiwan chapter and previously held the position of director of professional development for IIA Taiwan. Sherry also has extensive experience serving as Chief of Internal Auditor and Chief of Accounting for a public company in Taiwan. Before that, she worked as a Senior Auditor at KPMG. Sherry is widely recognized for inventing JCAATs, which were first released in London in 2017. She holds an MBA and various professional certifications, including CIA, CCSA, ICCP, CEAP, CFAP, ISO 14067:2018, ISO27001, ACDA, etc. ★內文試閱： ‧作者序 As the world enters the AI era, auditors face new challenges and opportunities that require them to use the right tools and technologies to stay ahead. With over 20 years of experience in audit and business data analytic, I have gained a deep understanding of the importance of transitioning from traditional audit operations to smart auditing that involves proactive warning or prediction using AI. Smart auditing enables businesses to obtain valuable insights and identify potential risks that traditional auditing methods may not detect. By using AI to analyze large amounts of structured and un-structured data, auditors can provide more accurate and insightful audits, as well as assist with compliance and risk management. JCAATs is a new audit software for smart auditing. It utilizes AI language Python and can run on Windows and MAC operating systems. It offers traditional computer-aided audit tools (CAATs) data analysis functions along with AI functions such as text mining, machine learning, and data crawling, resulting in smarter audit analysis. The software allows for the analysis of large amounts of data and an open data architecture that enables interfacing with various databases, cloud data sources, and different file types, making data collection and integration more convenient and faster. Additionally, the multiple language and visual user interface makes generating Python audit programs simple and easy, even for auditors not familiar with Python language. Integrating with open-source Python program resources enables more scalability and openness for audit programs, eliminating the limitations of only a few software programs. This textbook explains the use of technology such as big data analysis, text mining, and machine learning in auditing through practical cases. Readers will gain an understanding of data analysis and smart audit and their advancements. JCAATs, which includes data fusion technology and an OPEN DATA connector, helps auditors quickly obtain heterogeneous data for audit operations, enhancing effectiveness and efficiency. The textbook includes exercise data for practicing with JCAATs to fully experience intelligent auditing practices. It's suitable for professionals like accountants, auditors, legal and compliance personnel, risk management, and information security, as well as managers at all levels, college teachers, and students with data analysis needs. Sherry Huang ICCP, CEAP, CFAP, CIA, CCSA Jacksoft Ltd., Taipei, Taiwan 2023/03/15 ‧推薦序 This book is designed to be a comprehensive guide for learners to develop their skills in big data analysis, text mining, and machine learning using the JCAATs AI audit software. The book is structured to provide a progressive learning experience, with chapters covering different concepts and applications, as well as exercises and practice questions. The book also includes simulated independent audit case exercises to help learners apply what they have learned to real-world business environments and develop their problem-solving abilities. The operating manuals for each audit instruction enable teachers to deliver No Code courses that are more practical and aligned with real-world applications. Overall, this book aims to provide a powerful knowledge system for smart auditing and equip learners with the knowledge and skills needed for the modern workplace. This book provides an educational version of the JCAATs - AI audit software for trial use, with a multi-language interface. This allows students to install the software on their personal computers for operational practice and learning. Since the JCAATs software is based on Python, it is easier to incorporate external resources into advanced Read Code and Write Code teaching, providing students with the necessary tools to develop their skills in big data analysis, text mining, and machine learning for the future auditing. ‧摘文 To cultivate AI programming skills in business schools and other institutions, the International Computer Auditing Education Association (ICAEA) recommends starting with No Code. This approach allows students to develop audit applications to solve real-world problems without needing to write any code, giving them practical experience and enhancing their professional value. Once proficient in No Code, students can progress to Read Code training, where they gain an understanding of coding logic. Finally, Write Code training enables them to create their own AI applications. This approach prepares students for a future working environment centered on data analysis and smart auditing, where they can collaborate with AI auditing robots. As the AI era presents new challenges to the education of business professionals, colleges must adopt innovative and effective approaches to prepare their students for the workforce of the future. This book is designed to be a comprehensive guide for learners to develop their skills in big data analysis, text mining, and machine learning using the JCAATs AI audit software. The book is structured to provide a progressive learning experience, with chapters covering different concepts and applications, as well as exercises and practice questions. The book also includes simulated independent audit case exercises to help learners apply what they have learned to real-world business environments and develop their problem-solving abilities. The operating manuals for each audit instruction enable teachers to deliver No Code courses that are more practical and aligned with real-world applications.