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Introduction to Accounting Data Analytics and Visualization
  • Level Foundation
  • Duration 21 hours
  • Course by University of Illinois Urbana-Champaign
  • Offered by

About

Accounting has always been about analytical thinking. From the earliest days of the profession, Luca Pacioli emphasized the importance of math and order for analyzing business transactions. The skillset that accountants have needed to perform math and to keep order has evolved from pencil and paper, to typewriters and calculators, then to spreadsheets and accounting software. A new skillset that is becoming more important for nearly every aspect of business is that of big data analytics: analyzing large amounts of data to find actionable insights. This course is designed to help accounting students develop an analytical mindset and prepare them to use data analytic programming languages like Python and R. We've divided the course into three main sections. In the first section, we bridge accountancy to analytics. We identify how tasks in the five major subdomains of accounting (i.e., financial, managerial, audit, tax, and systems) have historically required an analytical mindset, and we then explore how those tasks can be completed more effectively and efficiently by using big data analytics. We then present a FACT framework for guiding big data analytics: Frame a question, Assemble data, Calculate the data, and Tell others about the results. In the second section of the course, we emphasize the importance of assembling data. Using financial statement data, we explain desirable characteristics of both data and datasets that will lead to effective calculations and visualizations. In the third, and largest section of the course, we demonstrate and explore how Excel and Tableau can be used to analyze big data. We describe visual perception principles and then apply those principles to create effective visualizations. We then examine fundamental data analytic tools, such as regression, linear programming (using Excel Solver), and clustering in the context of point of sale data and loan data. We conclude by demonstrating the power of data analytic programming languages to assemble, visualize, and analyze data. We introduce Visual Basic for Applications as an example of a programming language, and the Visual Basic Editor as an example of an integrated development environment (IDE).

Modules

About the Course

    • 2 Videos
    • 5 Readings
    • 1 Plugin
Show info about module content

2 Videos

  • Course Introduction
  • About Ronald Guymon

5 Readings

  • Syllabus
  • Glossary
  • About the Discussion Forums
  • ePub
  • Online Education at Gies College of Business

About Your Classmates

    • 1 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • Get to Know Your Fellow Learners

1 Readings

  • Update Your Profile

Module 1 Information

    • 1 Videos
    • 2 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • Make Connections to Topic

1 Videos

  • Module 1 Introduction

2 Readings

  • Module 1 Overview
  • Module 1 Readings

Lesson 1.1

    • 5 Videos
    • 1 Quiz
Show info about module content

5 Videos

  • 1.1.1 History and Future of Accounting
  • 1.1.2 The Importance of Data and Analytics in Accounting
  • 1.1.3 Humans' Relationship with Data
  • 1.1.4 Accountants' Role in Shaping How Data Is Used
  • 1.1.5 Data Analytics Tools: Spreadsheets vs. Data Science Languages

1 Quiz

  • Lesson 1.1 Knowledge Check

Lesson 1.2

    • 5 Videos
    • 1 Quiz
Show info about module content

5 Videos

  • 1.2.1 Advanced Data Analytics in Managerial Accounting Overview
  • 1.2.2 Advanced Data Analytics in Auditing Overview
  • 1.2.3 Advanced Data Analytics in Financial Accounting Overview
  • 1.2.4 Advanced Data Analytics in Taxes Overview
  • 1.2.5 Advanced Data Analytics in Systems Accounting Overview

1 Quiz

  • Lesson 1.2 Knowledge Check

Module 1 Conclusion

    • 1 Videos
    • 1 Quiz
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1 Videos

  • Module 1 Conclusion

1 Quiz

  • Introduction to Accountancy Analytics: Quiz

Module 2 Information

    • 1 Videos
    • 2 Readings
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1 Videos

  • Module 2 Introduction

2 Readings

  • Module 2 Overview
  • Module 2 Readings

Lesson 2.1

    • 2 Videos
    • 1 Quiz
Show info about module content

2 Videos

  • 2.1.1 Making Room for Empirical Enquiry
  • 2.1.2 System 1 vs. System 2 Mindset

1 Quiz

  • Lesson 2.1 Knowledge Check

Lesson 2.2

    • 3 Videos
    • 1 Quiz
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3 Videos

  • 2.2.1 Linking Core Courses to Analytical Thinking
  • 2.2.2 Inductive and Deductive Reasoning
  • 2.2.3 Advanced Analytics and the Art of Persuasion

1 Quiz

  • Lesson 2.2 Knowledge Check

Lesson 2.3

    • 5 Videos
    • 1 Quiz
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5 Videos

  • 2.3.1 FACT Framework: Frame the Question
  • 2.3.2 FACT Framework: Assemble the Data
  • 2.3.3 FACT Framework: Calculate Results
  • 2.3.4 FACT Framework: Tell Others About the Results
  • 2.3.5 FACT Framework Review

1 Quiz

  • Lesson 2.3 Knowledge Check

Module 2 Conclusion

    • 1 Videos
    • 1 Quiz
Show info about module content

1 Videos

  • Module 2 Conclusion

1 Quiz

  • Accounting Analysis and an Analytics Mindset: Quiz

Module 3 Information

    • 1 Videos
    • 2 Readings
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1 Videos

  • Module 3 Introduction: What is Data?

2 Readings

  • Module 3 Overview
  • Module 3 Readings

Lesson 3.1

    • 1 Videos
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1 Videos

  • 3.1.1 Characteristics that Make Data Useful for Decision Making

Lesson 3.2

    • 4 Videos
    • 1 Quiz
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4 Videos

  • 3.2.1 Structured vs. Unstructured Data
  • 3.2.2 Properties of a Tidy Dataframe
  • 3.2.3 Data Types
  • 3.2.4 Data Dictionaries

1 Quiz

  • Lesson 3.2 Knowledge Check

Lesson 3.3

    • 3 Videos
Show info about module content

3 Videos

  • 3.3.1 Wide Data vs. Long Data
  • 3.3.2 Merging Data
  • 3.3.3 Data Automation

Lesson 3.4

    • 2 Videos
    • 1 Quiz
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2 Videos

  • 3.4.1 Visualization Distributions
  • 3.4.2 Visualizing Data Relationships

1 Quiz

  • Lesson 3.4 Knowledge Check

Module 3 Conclusion

    • 1 Videos
    • 1 Quiz
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1 Videos

  • Module 3 Conclusion

1 Quiz

  • Data and Its Properties: Quiz

Module 4 Information

    • 1 Videos
    • 2 Readings
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1 Videos

  • Module 4 Introduction

2 Readings

  • Module 4 Overview
  • Module 4 Readings

Lesson 4.1

    • 3 Videos
    • 1 Quiz
Show info about module content

3 Videos

  • 4.1.1 Why Visualize Data?
  • 4.1.2 Visual Perception Principles
  • 4.1.3 Data Visualization Building Blocks

1 Quiz

  • Lesson 4.1 Knowledge Check

Lesson 4.2

    • 6 Videos
    • 1 Quiz
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6 Videos

  • 4.2.1 Basic Chart Data
  • 4.2.2 Scatter Plots
  • 4.2.3 Bar Charts
  • 4.2.4 Box and Whisker Plots
  • 4.2.5 Line Charts
  • 4.2.6 Maps

1 Quiz

  • Lesson 4.2 Knowledge Check

Lesson 4.3

    • 6 Videos
    • 1 Quiz
Show info about module content

6 Videos

  • 4.3.1 Financial Chart Data
  • 4.3.2 Waterfall Charts
  • 4.3.3 Candlestick Charts
  • 4.3.4 Treemaps and Sunburst Charts
  • 4.3.5 Sparklines and Facets
  • 4.3.6 Charts to Use Sparingly

1 Quiz

  • Lesson 4.3 Knowledge Check

Module 4 Conclusion

    • 1 Videos
    • 1 Quiz
    • 1 PeerReview
Show info about module content

1 Peer Review

  • Data Visualization 1: Peer Review Assignment

1 Videos

  • Module 4 Conclusion

1 Quiz

  • Data Visualization 1: Quiz

Module 5 Information

    • 1 Videos
    • 2 Readings
Show info about module content

1 Videos

  • Module 5 Introduction

2 Readings

  • Module 5 Overview
  • Module 5 Readings

Lesson 5.1

    • 5 Videos
Show info about module content

5 Videos

  • 5.1.1 Getting Started with Tableau
  • 5.1.2 Scatter Plots in Tableau - 1
  • 5.1.3 Scatter Plots in Tableau - 2
  • 5.1.4 Bar Charts and Histograms in Tableau
  • 5.1.5 Box Plots and Line Charts in Tableau

Lesson 5.2

    • 2 Videos
    • 1 Quiz
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2 Videos

  • 5.2.1 Adding Dimensions in Tableau
  • 5.2.2 Facets and Groups in Tableau

1 Quiz

  • Lesson 5.2 Knowledge Check

Lesson 5.3

    • 3 Videos
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3 Videos

  • 5.3.1 Data Joins in Tableau
  • 5.3.2 Tableau Analytics - Forecasts
  • 5.3.3 Tableau Analytics - Clusters and Confidence Intervals

Lesson 5.4

    • 1 Videos
    • 1 Quiz
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1 Videos

  • 5.4.1 Communicating Tableau Analyses

1 Quiz

  • Lesson 5.4 Knowledge Check

Module 5 Conclusion

    • 1 Videos
    • 1 Quiz
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1 Videos

  • Module 5 Conclusion

1 Quiz

  • Data Visualization 2: Quiz

Module 6 Information

    • 1 Videos
    • 2 Readings
Show info about module content

1 Videos

  • Module 6 Introduction

2 Readings

  • Module 6 Overview
  • Module 6 Readings

Lesson 6.1

    • 4 Videos
    • 1 Quiz
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4 Videos

  • 6.1.1 Framing a Question: Larry's Commissary
  • 6.1.2 Assembling Data
  • 6.1.3 Data Analysis ToolPak and Descriptive Statistics
  • 6.1.4 Correlation

1 Quiz

  • Lesson 6.1 Knowledge Check

Lesson 6.2

    • 3 Videos
    • 1 Quiz
Show info about module content

3 Videos

  • 6.2.1 Linear Models
  • 6.2.2 Simple Regression
  • 6.2.3 Regression Diagnostics 1: Regression Summary, ANOVA, and Coefficient Estimates

1 Quiz

  • Lesson 6.2 Knowledge Check

Lesson 6.3

    • 3 Videos
Show info about module content

3 Videos

  • 6.3.1 Multiple Regression
  • 6.3.2 Regression Diagnostics 2: Predicted Values, Residuals, and Standardized Residuals
  • 6.3.3 Regression Diagnostics 3: Line Fit Plots, Adjusted R Square, and Heat Maps for P-Values

Lesson 6.4

    • 1 Videos
    • 1 Quiz
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1 Videos

  • 6.4.1 Making a Forecast with a Linear Model

1 Quiz

  • Lesson 6.4 Knowledge Check

Module 6 Conclusion

    • 1 Videos
    • 1 Quiz
    • 1 PeerReview
Show info about module content

1 Peer Review

  • Analytic Tools in Excel 1: Peer Review Assignment

1 Videos

  • Module 6 Conclusion

1 Quiz

  • Analytic Tools in Excel 1: Quiz

Module 7 Information

    • 1 Videos
    • 2 Readings
Show info about module content

1 Videos

  • Module 7 Introduction

2 Readings

  • Module 7 Overview
  • Module 7 Readings

Lesson 7.1

    • 5 Videos
    • 1 Quiz
Show info about module content

5 Videos

  • 7.1.1 Polynomial Regression Models
  • 7.1.2 Categorical Variables
  • 7.1.3 Multiple Indicator Variables
  • 7.1.4 Interaction Terms
  • 7.1.5 Regression Summary

1 Quiz

  • Lesson 7.1 Knowledge Check

Lesson 7.2

    • 2 Videos
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2 Videos

  • 7.2.1 Optimization with Excel Solver
  • 7.2.2 Solver Constraints and Reports

Lesson 7.3

    • 3 Videos
    • 1 Quiz
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3 Videos

  • 7.3.1 Logit Transformation
  • 7.3.2 Simple Logistic Regression
  • 7.3.3 Logistic Regression Accuracy

1 Quiz

  • Lesson 7.3 Knowledge Check

Module 7 Conclusion

    • 1 Videos
    • 1 Quiz
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1 Videos

  • Module 7 Conclusion

1 Quiz

  • Analytic Tools in Excel 2: Quiz

Module 8 Information

    • 1 Videos
    • 2 Readings
Show info about module content

1 Videos

  • Module 8 Introduction

2 Readings

  • Module 8 Overview
  • Module 8 Readings

Lesson 8.1

    • 3 Videos
    • 1 Quiz
Show info about module content

3 Videos

  • 8.1.1 Recording Macros
  • 8.1.2 Basics of VB Editor
  • 8.1.3 Basics of VBA

1 Quiz

  • Lesson 8.1 Knowledge Check

Lesson 8.2

    • 3 Videos
    • 1 Quiz
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3 Videos

  • 8.2.1 For Loops, Variables, Index Numbers, and Last Rows
  • 8.2.2 Programming Hints
  • 8.2.3 Conditional Statements

1 Quiz

  • Lesson 8.2 Knowledge Check

Lesson 8.3

    • 5 Videos
    • 1 Quiz
Show info about module content

5 Videos

  • 8.3.1 Macro for Creating Multiple Histograms
  • 8.3.2 Clustering Overview
  • 8.3.3 K-Means Clustering in Excel
  • 8.3.4 K-Means Clustering Macro
  • 8.3.5 Clustering On a Larger Scale

1 Quiz

  • Lesson 8.3 Knowledge Check

Module 8 Conclusion

    • 2 Videos
    • 2 Readings
    • 1 Quiz
    • 1 Plugin
Show info about module content

2 Videos

  • Module 8 Conclusion
  • Learn on Your Terms

2 Readings

  • Congratulations on completing the course!
  • Get Your Course Certificate

1 Quiz

  • Automation in Excel: Quiz
Ronald Guymon
Instructor

Ronald Guymon