Introduction to Accounting Data Analytics and Visualization from Coursera

What's inside

Syllabus

Course Introduction and Module 1: Introduction to Accountancy Analytics

In this module, you will become familiar with the course, your instructor and your classmates, and our learning environment. This orientation module will also help you obtain the technical skills required to navigate and be successful in this course.

Module 1: Introduction to Accountancy Analytics

In this module, you will learn how the accounting profession has evolved. You will recognize how data analytics has influenced the accounting profession and how accountants have the ability to impact how data analytics is used in the profession, as well as in an organization. Finally, you will learn how data analytics is influencing the different subdomains within accounting.

Module 2: Accounting Analysis and an Analytics Mindset

In this module, you will learn to recognize the importance of making room for empirical enquiry in decision making. You will explore characteristics of an analytical mindset in business and accounting contexts, and link those to your core courses. You will then evaluate a framework for making data-driven decisions using big data.

Module 3: Data and its Properties

This module looks at specific characteristics of data that make it useful for decision making.

Module 4: Data Visualization 1

In this module, you will learn fundamental principles that underlie data visualizations. Using those principles, you will identify use cases for different charts and learn how to build those charts in Excel. You will then use your knowledge of different charts to identify alternative charts that are better suited for directing attention.

Module 5: Data Visualization 2

In this module, you’ll learn how to use Tableau to do with data what spies do when observing their surroundings: get an overview of the data, narrow in on certain aspects of the data that seem abnormal, and then analyze the data. Tableau is a great tool for facilitating the overview, zoom, then filter details-on-demand approach. Tableau is a lot like a more powerful version of Excel's pivot table and pivot chart functionality.

Module 6: Analytic Tools in Excel 1

In this module, you'll be guided through a mini-case study that will illustrate the first three parts of the FACT model, with a focus on the C, or calculations part of the FACT model. First, you will perform a correlation analysis to identify two-way relationships, and analyze correlations using a correlation matrix and scatter plots. You will then build on your knowledge of correlations and learn how to perform regression analysis in Excel. Finally, you will learn how to interpret and evaluate the diagnostic metrics and plots of a regression analysis.

Module 7: Analytic Tools in Excel 2

In this module, you’ll learn how the regression algorithm can be applied to fit a wide variety of relationships among data. Specifically, you’ll learn how to set up the data and run a regression to estimate the parameters of nonlinear relationships, categorical independent variables. You’ll also investigate if the effect of an independent variable depends on the level of another independent variable by including interaction terms in the multiple regression model. Another aspect of this module is learning how to evaluate models, regression or otherwise, to find the most favorable levels of the independent variables. For models that explain revenue, the most favorable levels of the independent variables will maximize revenue. In contrast, if you have a model that describes costs, like a budget, then the most favorable levels of the independent variables will minimize costs. Optimizing models can be difficult because there are so many inputs and constraints that need to be managed. In this module, you’ll learn how to use the Solver Add-In to find the optimal level of inputs. For some models, the dependent variable is a binary variable that has only two values, such as true/false, win/lose, or invest/not invest. In these situations, a special type of regression, called logistic regression, is used to predict how each observation should be classified. You’ll learn about the logit transformation that’s used to convert a binary outcome to a linear relationship with the independent variables. Excel doesn’t have a built-in logistic regression tool, so you’ll learn how to manually design a logistic regression model, and then optimize the parameters using the Solver Add-In tool.

Module 8: Automation in Excel

The lessons in this module are organized around several useful tasks, including stacking multiple dataframes together into one dataframe, creating multiple histograms to accompany the descriptive statistics, and learning how to perform k-means clustering. After going through this module, you’ll not only gain a foundation to help you understand coding, but you’ll also learn more about analyzing financial data. Along the way, I hope that you’ll also pick up on a few other useful Excel functions.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Suitable for Accounting students who want to develop an analytical mindset and prepare to utilize data analytic programming languages

Emphasizes the importance of assembling data effectively

Leverages Excel and Tableau effectively for analyzing data

Demonstrates fundamental data analytic tools like regression, linear programming, and clustering

Introduces Visual Basic for Applications as an example of a programming language and Visual Basic Editor as an example of an integrated development environment (IDE)

Reviews summary

Revered accounting data analytics course

Learners say this course is largely positive, providing a great overview of accounting data analytics and visualization with an engaging and interactive learning style. Students appreciate the practical skills and clear explanations they gain from the helpful video lectures, assignments, and hands-on exercises.

Knowledgeable and passionate instructor.

"I think the course instructor was incredibly knowledgeable and easy to follow, and I think he made the course fun too!"

"The way the lecturer teaches is very passionate and very interesting"

Engaging video lectures, assignments, and hands-on exercises.

"I really enjoyed the course and the lecture was very interactive, clear & precise in such a way i felt i was in a classroom."

"Very insightful session on how to get the best picture out of huge data. I certainly like the homework as it gave me time to practice on certain items."

Focus on practical skills in data analytics and visualization.

"Great course in learning VBA, Pivot Table, Tableau, Regression and Logistical Regression, Analytical Mindset with the FACT Framework"

"The practice exercises were just great!"

Well-explained and easy-to-understand video lessons.

"Prof was very clear and everything is explained in fairly simple terms, in an easy to understand way."

"They really took the time to explain the why behind the concepts, and show how to manually calculate."

Covers a wide range of topics, which may be a bit lengthy for some learners.

"Covers a nice foundation for data analytics principles, terms, and excel and tableau software. Only thing is it is a bit lengthy, don't try to rush this course."

"The course teaches a lot of useful data analytics and visualization techniques which will prove to be useful in the future. The only complaint I have is that for the peer review 2, the data provided to us is in csv format."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Accounting Data Analytics and Visualization with these activities:

Review concepts of accounting

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Reviewing the fundamentals of accounting will help you to better understand the material that will be covered in the course.

Browse courses on Accounting Concepts

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Review your notes from previous accounting courses.
Take practice quizzes on accounting concepts.
Read articles and blog posts about accounting.

Form a study group

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Enhance your understanding of course concepts by engaging in discussions and sharing insights with peers, fostering a collaborative learning environment.

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Find a group of classmates with complementary skills and interests.
Establish a regular meeting schedule and set clear goals for each session.
Take turns presenting topics, leading discussions, and providing feedback.

Solve regression problems

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Reinforce your understanding of regression analysis by solving practice problems, solidifying your skills in this area.

Browse courses on Regression Analysis

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Find practice problems online or in textbooks.
Solve the problems step-by-step, showing your work.
Check your answers against provided solutions or consult with a tutor or instructor if needed.

Six other activities

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Explore advanced Excel functions

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Expand your proficiency in Excel by exploring advanced functions that can enhance your data analysis and manipulation abilities.

Browse courses on Excel

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Identify specific Excel functions that align with your learning goals.
Find online tutorials or documentation on those functions.
Follow the tutorials step-by-step, practicing the functions in your own spreadsheets.

Join a study group

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Joining a study group will allow you to discuss the course material with other students and to get help with any difficult concepts.

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Find a study group that is appropriate for your level of experience.
Attend the study group meetings.
Participate in the discussions.

Build a data visualization dashboard

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Test your data visualization skills by creating a comprehensive dashboard that effectively communicates insights from a given dataset, showcasing your proficiency in presenting data in a visually compelling way.

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Choose a dataset and identify the key insights you want to convey.
Design the layout of your dashboard, including the appropriate charts and graphs.
Develop the dashboard using Tableau or a similar tool.
Present your dashboard to others for feedback and refinement.

Develop a case study analysis

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Demonstrate your ability to apply course concepts to real-world scenarios by developing a comprehensive analysis of a business case study, showcasing your analytical and problem-solving skills.

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Choose a case study that is relevant to the course topics.
Analyze the case study using the concepts and techniques covered in the course.
Develop a written report or presentation that outlines your analysis and recommendations.

Develop a financial plan for a small business

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Developing a financial plan for a small business will help you to apply the concepts that you have learned in the course to a real-world situation.

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Gather information about the small business.
Analyze the small business's financial situation.
Develop a financial plan for the small business.
Present the financial plan to the small business owner.

Contribute to an open-source accounting project

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Contributing to an open-source accounting project will allow you to learn about the latest accounting technologies and to give back to the accounting community.

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Find an open-source accounting project that you are interested in.
Contribute to the project.
Submit a pull request.

Career center

Learners who complete Introduction to Accounting Data Analytics and Visualization will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course provides a solid foundation for this role by teaching how to use Excel and Tableau to analyze large datasets. Graduates of this course will be especially well prepared for the tasks that Data Analysts perform, which often require strong analytical skills and the ability to communicate insights effectively.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models to solve real-world problems. This course provides a foundation for this role by teaching how to use machine learning algorithms to analyze data and make predictions. Graduates of this course will be especially well prepared for the tasks that Machine Learning Engineers perform, which often require strong analytical skills and the ability to communicate effectively with both technical and non-technical audiences.

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Statistician

Statisticians collect, analyze, and interpret data to help businesses make informed decisions. This course provides a foundation for this role by teaching how to use statistical methods to analyze data and draw conclusions. Graduates of this course will be especially well prepared for the tasks that Statisticians perform, which often require strong analytical skills and the ability to communicate effectively with both technical and non-technical audiences.

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Data Scientist

Data Scientists use data to solve complex problems and make predictions. This course provides a foundation for this role by teaching how to analyze data and build predictive models. Graduates of this course will be especially well prepared for the tasks that Data Scientists perform, which often require strong analytical skills and the ability to communicate effectively with technical and non-technical audiences.

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Data Engineer

Data Engineers build and maintain the infrastructure that is used to store and process data. This course provides a foundation for this role by teaching how to use data engineering tools and technologies to manage data. Graduates of this course will be especially well prepared for the tasks that Data Engineers perform, which often require strong analytical skills and the ability to communicate effectively with both technical and non-technical audiences.

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Business Analyst

Business Analysts help businesses improve their performance by identifying and solving problems. This course provides a foundation for this role by teaching how to use data analysis to understand business processes and make recommendations for improvement. Graduates of this course will be especially well prepared for the tasks that Business Analysts perform, which often require strong analytical skills and the ability to communicate effectively with both technical and non-technical audiences.

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Software Engineer

Software Engineers design, develop, and maintain software applications. This course provides a foundation for this role by teaching how to use programming languages and software development tools to build software applications. Graduates of this course will be especially well prepared for the tasks that Software Engineers perform, which often require strong analytical skills and the ability to communicate effectively with both technical and non-technical audiences.

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Management Consultant

Management Consultants help businesses improve their performance by providing advice on strategy, operations, and technology. This course provides a foundation for this role by teaching how to analyze data and make recommendations for improvement. Graduates of this course will be especially well prepared for the tasks that Management Consultants perform, which often require strong analytical skills and the ability to communicate effectively with clients.

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Investment Analyst

Investment Analysts are responsible for evaluating and recommending investments. This course provides a foundation for this role by teaching how to analyze financial data and make investment recommendations. Graduates of this course will be especially well prepared for the tasks that Investment Analysts perform, which often require strong analytical skills and the ability to communicate effectively with clients.

See salaries and explore the career path for Investment Analyst

Risk Analyst

Risk Analysts are responsible for identifying and managing risks that could impact a business. This course provides a foundation for this role by teaching how to analyze data and identify potential risks. Graduates of this course will be especially well prepared for the tasks that Risk Analysts perform, which often require strong analytical skills and the ability to communicate effectively with management.

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Auditor

Auditors are responsible for examining and evaluating financial records to ensure that they are accurate and compliant with regulations. This course provides a foundation for this role by teaching how to analyze financial data and identify potential risks. Graduates of this course will be especially well prepared for the tasks that Auditors perform, which often require strong analytical skills and the ability to understand complex financial transactions.

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Forensic Accountant

Forensic Accountants are responsible for investigating financial crimes and fraud. This course provides a foundation for this role by teaching how to analyze financial data and identify potential fraud. Graduates of this course will be especially well prepared for the tasks that Forensic Accountants perform, which often require strong analytical skills and the ability to communicate effectively with law enforcement and legal professionals.

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Financial Planner

Financial Planners help individuals and families plan for their financial future. This course provides a foundation for this role by teaching how to analyze financial data and make recommendations for investment and retirement planning. Graduates of this course will be especially well prepared for the tasks that Financial Planners perform, which often require strong analytical skills and the ability to communicate effectively with clients.

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Financial Analyst

Financial Analysts typically help companies make sound business decisions by providing insights into financial data. This course helps build a foundation for this role by teaching how to prepare, analyze, and present financial information. Graduates of this course will be especially well prepared for the tasks that Financial Analysts perform, which often require a deep understanding of financial markets and the ability to interpret financial statements.

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Tax Accountant

Tax Accountants are responsible for preparing and filing tax returns for individuals and businesses. This course provides a foundation for this role by teaching how to analyze tax laws and regulations. Graduates of this course will be especially well prepared for the tasks that Tax Accountants perform, which often require strong analytical skills and the ability to stay up-to-date on tax laws.

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