Data Analytics Using Microsoft® Excel®: With Accounting and Finance Datasets
Custom Version 2.0.1
By Joseph M. Manzo
Jason P Sharp
Included Supplements
Key Features
- This version is updated to align with Excel 2016.
- Early chapters explain how to conceptualize, design, and maintain the integrity of data analytics projects in any context, not just finance or accounting. Compatible with general technology courses that are not content specific.
- Can be used stand alone or as a supplemental resource.
- Datasets and projects are compatible with many accounting and finance courses, but can also support an interdisciplinary focus.
- Clearly and simply walks students through core concepts. No prior accounting or finance coursework is required.
Students
- Online Access Price
- $36.95
- Color Printed Textbook with Online Access Price
- $63.95
This textbook is suitable as either a core text for using Excel 2016 in an introductory data analytics course or as a supplement to many basic through intermediate accounting or finance courses. May also be assigned to students who need exposure or a refresher on how to use the Excel 2016 application in general.
Data Analytics Using Microsoft Excel With Accounting and Finance Datasets provides students with the opportunity to learn basic skills needed to execute many personal and professional activities using Excel 2016. This clear, easy-to-follow text also prepares learners to master more advanced skills using Excel. Heavy emphasis is placed on how to efficiently navigate big datasets and use the keyboard to access commands during the design process. Author-narrated videos embedded throughout the digital reader explain concepts and operations, adding an engaging audio and visual richness to the written explanations and exercises.
Extensive datasets included in the book are drawn from accounting and finance scenarios and provide learners with a basis for conceptualizing and designing data analytics projects with the highest level of integrity. Data visualization skills are also introduced and reinforced throughout.
- About the Author
- Acknowledgments
- Dedication
- Preface
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Chapter 1: Introduction to Data Analytics and Microsoft Excel
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Chapter 2: Essential Skills for Basic Data Analytics Projects
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Chapter 3: Data Analytics Techniques for Basic Projects
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Chapter 4: Using Mathematical Outputs for Analytics
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Chapter 5: Scenario Analytics
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Chapter 6: Exception Analytics
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Chapter 7: Summarizing Exception Analytics
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Chapter 8: Big Datasets Case: Investigating Fraud
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Chapter 9: Charts for Presentations and Data Visualization
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Chapter 10: Information Systems
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Chapter 11: Business Intelligence and Databases
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Chapter 12: Data Cleaning
FlatWorld Homework
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Instructor’s Manual
The Instructor’s Manual guides you through the main concepts of each chapter and important elements such as learning objectives, key terms, and key takeaways. Can include answers to chapter exercises, group activity suggestions, and discussion questions.
PowerPoint Lecture Notes
A PowerPoint presentation highlighting key learning objectives and the main concepts for each chapter are available for you to use in your classroom. You can either cut and paste sections or use the presentation as a whole.
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Other Supplements
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