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Solution Manual for Data and Analytics in
Accounting: An Integrated Approach 1st Edition
CHAPTER 1
DATA AND ANALYTICS IN THE ACCOUNTING PROFESSION
TU
Learning Objectives:
LO 1.1: Summarize how advances in data and technology are impacting accounting professionals.
LO 1.2: Describe the stages of the data analysis process.
LO 1.3: Identify the skills necessary to perform data analysis.
TO
LO 1.4: Explain how to apply a data analytics mindset during the data analysis process.
ANSWERS TO MULTIPLE CHOICE QUESTIONS
LO 1.2, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
1. A
R
Leverage Technology to Develop and Enhance Functional Competencies
LO 1.1, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
7. D
2. C LO 1.2, BT: C, Difficulty: Medium, TOT: 3 min, AACSB: Analytic, AICPA FC:
G
LO 1.1, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
Leverage Technology to Develop and Enhance Functional Competencies
8. C
3. C LO 1.2, BT: C, Difficulty: Medium, TOT: 3 min, AACSB: Analytic, AICPA FC:
LO 1.2, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
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Leverage Technology to Develop and Enhance Functional Competencies
9. A
4. B LO 1.3, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
LO 1 2, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
Leverage Technology to Develop and Enhance Functional Competencies
R
10.D
5. B LO 1.3, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
LO 1.2, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
Leverage Technology to Develop and Enhance Functional Competencies
U
11.B
6. C
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LO 1.3, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
14.A
LO 1.4, BT: C, Difficulty: Medium, TOT: 3 min, AACSB: Analytic, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
12.A
LO 1.4, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
15.B
LO 1.4, BT: C, Difficulty: Medium, TOT: 3 min, AACSB: Analytic, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
13.D
LO 1.4, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
TU
ANSWERS TO REVIEW QUESTIONS
1. Both the CPA exam and the CMA exam have added data analytic content to their exams. This is in
TO
response to what new professionals need to know as they enter the accounting profession. The CPA
Exam Evolution is a strong indication of how the accounting profession is changing. The new CPA exam
will have more technology and data analytics questions in the Core exam, as well as the Discipline
exams.
LO 1.1, BT: K, Difficulty: Easy, TOT: 6 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
R
2.
Changes Accounting Practice Area
1. Ability to use entire data sets to identify ANS: a. Auditing, c. Managerial accounting
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exceptions, anomalies, and outliers
2. Automation of manual processes ANS: a., b., c., d. (All areas)
3. Automation of journal entries ANS: b. Financial accounting
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4. Risk identification ANS:. a. Auditing, c. Managerial accounting
5. Forecasting ANS: b. Financial accounting, c. Managerial
accounting
6. Compliance reporting ANS: d. Tax accounting
R
LO 1.1, BT: C, Difficulty: Medium, TOT: 8 min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
3. Data are raw facts and figures. Technology helps covert that data into information. Information is the
U
knowledge gained from analyzing the data.
LO 1.1, BT: C, Difficulty: Medium, TOT: 6 min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
4.
Purpose Method
1. Understanding what is happening currently ANS: a. Descriptive
and what has happened in the past.
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2. Understanding what should happen to meet ANS: d. Prescriptive
our goals and objectives.
3. Understanding what might happen in the ANS: c. Prescriptive
future.
4. Understanding why something happened. ANS: b. Diagnostic
LO 1.2, BT: C, Difficulty: Medium, TOT: 6 min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
5. The first step is to identify the motivation for the analysis. The motivation for a project is the why the
TU
analysis is being performed. It is important to understand the reason for the analysis before beginning
the analysis.
The second step is to set an objective. In other words, “What is the goal of the analysis?” This step will
help articulate the goal and specific questions that will be analyzed.
The third step is to develop a strategy. In this step, we determine the data and analysis methods
TO
necessary to achieve the project’s goal.
LO 1.2, BT: K, Difficulty: Easy, TOT: 8 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
6. Extracting is the process in which data is retrieved from a source. This could involve downloading an
Excel file or extracting data from a database or a data warehouse.
R
Transforming the data occurs when data is cleaned, restructured, and/or integrated prior to using it for
analysis.
Loading data is the process of importing transformed data into the software used to perform analyses.
G
LO 1.2, BT: K, Difficulty: Easy, TOT: 8 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
U
7.
Example Data Analysis Process Stage
1. Develop a model to calculate contribution ANS: b. Analyze
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margin.
2. Get data from a database. ANS: b. Analyze
3. Upload data into analysis software. ANS:b. Analyze
4. Determine the objective of the analysis. ANS: a. Plan
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5. Create a forecast of net income. ANS: b. Analyze
6. Identify the data needed for analysis. ANS: a. Plan
7. Identify relationships within the data. ANS: b. Analyze
8. Create a visualization to show the results of ANS: c. Report
the analyses.
9. Identify sales patterns. ANS: b. Analyze
LO 1.2, BT: C, Difficulty: Medium, TOT: 12 min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
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8. A data analytics mindset is the habit critically thinking through the planning, analysis, and
interpretation of data results before making and communicating a professional choice or
decision. Individuals with a data analytics mindset are inquisitive. They always ask “why” when
interpreting results, are open to learning new technologies, and take the time to evaluate their own
thinking.
LO 1.3, BT: C, Difficulty: Medium, TOT: 6min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
9. The ability to communicate well is important in all areas of accounting. In data analytics it is
important to have good communication skills to explain the results of analyses so others can understand
TU
and act if needed.
LO 1.3, BT: C, Difficulty: Medium, TOT: 6min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
10. 10.
Definition Skill
TO
1. Willingness to try new technology. ANS: c. Technological agility
2. The ability to read, write, and communicate ANS: b. Data literacy
data in context.
3. Ability to create effective data visualizations ANS: d. Communication
4. Disciplined reasoning used to investigate, ANS: a. Critical thinking
understand, and evaluate an event, opportunity,
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or an issue.
LO1. 3, BT: K, Difficulty: Easy, TOT: 8min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies.
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11. 11.
• Stakeholders: Understand the internal and external parties impacted by the data analysis
results.
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• Purpose: Determine the reason for the analysis.
• Alternatives: Evaluate and rank all potential data and analysis choices during the data analysis
process.
R
• Risks: Consider risks to the data and the analysis choices, including assumptions and potential
biases.
• Knowledge: Identify and acquiring the knowledge necessary to properly prepare and interpret
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the analyses.
• Self-reflection: Review decisions and processes for lessons learned and apply them to future
projects.
LO 1. 4, BT: C, Difficulty: Medium, TOT: 10min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
12. Student answers will vary. General examples follow.
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Solution Manual for Data and Analytics in
Accounting: An Integrated Approach 1st Edition
CHAPTER 1
DATA AND ANALYTICS IN THE ACCOUNTING PROFESSION
TU
Learning Objectives:
LO 1.1: Summarize how advances in data and technology are impacting accounting professionals.
LO 1.2: Describe the stages of the data analysis process.
LO 1.3: Identify the skills necessary to perform data analysis.
TO
LO 1.4: Explain how to apply a data analytics mindset during the data analysis process.
ANSWERS TO MULTIPLE CHOICE QUESTIONS
LO 1.2, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
1. A
R
Leverage Technology to Develop and Enhance Functional Competencies
LO 1.1, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
7. D
2. C LO 1.2, BT: C, Difficulty: Medium, TOT: 3 min, AACSB: Analytic, AICPA FC:
G
LO 1.1, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
Leverage Technology to Develop and Enhance Functional Competencies
8. C
3. C LO 1.2, BT: C, Difficulty: Medium, TOT: 3 min, AACSB: Analytic, AICPA FC:
LO 1.2, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
U
Leverage Technology to Develop and Enhance Functional Competencies
9. A
4. B LO 1.3, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
LO 1 2, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
Leverage Technology to Develop and Enhance Functional Competencies
R
10.D
5. B LO 1.3, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
LO 1.2, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
Leverage Technology to Develop and Enhance Functional Competencies
U
11.B
6. C
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LO 1.3, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
14.A
LO 1.4, BT: C, Difficulty: Medium, TOT: 3 min, AACSB: Analytic, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
12.A
LO 1.4, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
15.B
LO 1.4, BT: C, Difficulty: Medium, TOT: 3 min, AACSB: Analytic, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
13.D
LO 1.4, BT: K, Difficulty: Easy, TOT: 2 min, AACSB: Knowledge, AICPA FC:
Leverage Technology to Develop and Enhance Functional Competencies
TU
ANSWERS TO REVIEW QUESTIONS
1. Both the CPA exam and the CMA exam have added data analytic content to their exams. This is in
TO
response to what new professionals need to know as they enter the accounting profession. The CPA
Exam Evolution is a strong indication of how the accounting profession is changing. The new CPA exam
will have more technology and data analytics questions in the Core exam, as well as the Discipline
exams.
LO 1.1, BT: K, Difficulty: Easy, TOT: 6 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
R
2.
Changes Accounting Practice Area
1. Ability to use entire data sets to identify ANS: a. Auditing, c. Managerial accounting
G
exceptions, anomalies, and outliers
2. Automation of manual processes ANS: a., b., c., d. (All areas)
3. Automation of journal entries ANS: b. Financial accounting
U
4. Risk identification ANS:. a. Auditing, c. Managerial accounting
5. Forecasting ANS: b. Financial accounting, c. Managerial
accounting
6. Compliance reporting ANS: d. Tax accounting
R
LO 1.1, BT: C, Difficulty: Medium, TOT: 8 min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
3. Data are raw facts and figures. Technology helps covert that data into information. Information is the
U
knowledge gained from analyzing the data.
LO 1.1, BT: C, Difficulty: Medium, TOT: 6 min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
4.
Purpose Method
1. Understanding what is happening currently ANS: a. Descriptive
and what has happened in the past.
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2. Understanding what should happen to meet ANS: d. Prescriptive
our goals and objectives.
3. Understanding what might happen in the ANS: c. Prescriptive
future.
4. Understanding why something happened. ANS: b. Diagnostic
LO 1.2, BT: C, Difficulty: Medium, TOT: 6 min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
5. The first step is to identify the motivation for the analysis. The motivation for a project is the why the
TU
analysis is being performed. It is important to understand the reason for the analysis before beginning
the analysis.
The second step is to set an objective. In other words, “What is the goal of the analysis?” This step will
help articulate the goal and specific questions that will be analyzed.
The third step is to develop a strategy. In this step, we determine the data and analysis methods
TO
necessary to achieve the project’s goal.
LO 1.2, BT: K, Difficulty: Easy, TOT: 8 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
6. Extracting is the process in which data is retrieved from a source. This could involve downloading an
Excel file or extracting data from a database or a data warehouse.
R
Transforming the data occurs when data is cleaned, restructured, and/or integrated prior to using it for
analysis.
Loading data is the process of importing transformed data into the software used to perform analyses.
G
LO 1.2, BT: K, Difficulty: Easy, TOT: 8 min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
U
7.
Example Data Analysis Process Stage
1. Develop a model to calculate contribution ANS: b. Analyze
R
margin.
2. Get data from a database. ANS: b. Analyze
3. Upload data into analysis software. ANS:b. Analyze
4. Determine the objective of the analysis. ANS: a. Plan
U
5. Create a forecast of net income. ANS: b. Analyze
6. Identify the data needed for analysis. ANS: a. Plan
7. Identify relationships within the data. ANS: b. Analyze
8. Create a visualization to show the results of ANS: c. Report
the analyses.
9. Identify sales patterns. ANS: b. Analyze
LO 1.2, BT: C, Difficulty: Medium, TOT: 12 min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
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8. A data analytics mindset is the habit critically thinking through the planning, analysis, and
interpretation of data results before making and communicating a professional choice or
decision. Individuals with a data analytics mindset are inquisitive. They always ask “why” when
interpreting results, are open to learning new technologies, and take the time to evaluate their own
thinking.
LO 1.3, BT: C, Difficulty: Medium, TOT: 6min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
9. The ability to communicate well is important in all areas of accounting. In data analytics it is
important to have good communication skills to explain the results of analyses so others can understand
TU
and act if needed.
LO 1.3, BT: C, Difficulty: Medium, TOT: 6min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
10. 10.
Definition Skill
TO
1. Willingness to try new technology. ANS: c. Technological agility
2. The ability to read, write, and communicate ANS: b. Data literacy
data in context.
3. Ability to create effective data visualizations ANS: d. Communication
4. Disciplined reasoning used to investigate, ANS: a. Critical thinking
understand, and evaluate an event, opportunity,
R
or an issue.
LO1. 3, BT: K, Difficulty: Easy, TOT: 8min, AACSB: Knowledge, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies.
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11. 11.
• Stakeholders: Understand the internal and external parties impacted by the data analysis
results.
U
• Purpose: Determine the reason for the analysis.
• Alternatives: Evaluate and rank all potential data and analysis choices during the data analysis
process.
R
• Risks: Consider risks to the data and the analysis choices, including assumptions and potential
biases.
• Knowledge: Identify and acquiring the knowledge necessary to properly prepare and interpret
U
the analyses.
• Self-reflection: Review decisions and processes for lessons learned and apply them to future
projects.
LO 1. 4, BT: C, Difficulty: Medium, TOT: 10min, AACSB: Analytic, AICPA FC: Leverage Technology to Develop and Enhance Functional Competencies
12. Student answers will vary. General examples follow.
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