Solution Manual
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for Data and Analytics in Accounting An Integrated Approach 1e Ann C.
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f4 Dzuranin, Guido Geerts, Margarita Lenk
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Prose1 Stuvia
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,https://www.stuvia.com/user/Prose1
CHAPTER 1 f4
DATA AND ANALYTICS IN THE ACCOUNTING
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PROFESSION f4
Learning Objectives: f4
LO 1.1: Summarize how advances in data and technology are impacting accounting professionals.
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LO 1.2: Describe the stages of the data analysis process.
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LO 1.3: Identify the skills necessary to perform data analysis.
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LO 1.4: Explain how to apply a data analytics mindset during the data analysis process.
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ANSWERS TO MULTIPLE CHOICE QUESTIONS f4 f4 f4 f4
LO f41.2, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA f4FC:
1. f 4 A f 4 Leverage f4 Technology f 4 to f 4 Develop f4and f4 Enhance f4 Functional f4 Competencies
LO f 4 1.1, f 4 BT: f 4 K, f 4 Difficulty: f 4 Easy, f 4 TOT: f 4 2 f 4 min, f 4 AACSB:
f 4 Knowledge, f 4 AICPA f 4 FC: f 4 Leverage f4Technology f4to f4Develop f4and
f4Enhance f4Functional f4Competencies
7. f 4 D
LO f41.2, f4BT: f4C, f4Difficulty: f4Medium, f4TOT: f43 f4min, f4AACSB: f4Analytic, f4AICPA f4FC:
2. f 4 C f 4 Leverage f4 Technology f 4 to f 4 Develop f4 and f4 Enhance f4 Functional f4 Competencies
LO f41.1, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA
f4FC: f 4 Leverage f4 Technology f4 to f 4 Develop f4 and f4 Enhance f4 Functional
8. f 4 C
f4 Competencies
LO f41.2, f4BT: f4C, f4Difficulty: f4Medium, f4TOT: f43 f4min, f4AACSB: f4Analytic, f4AICPA f4FC:
f 4 Leverage f4 Technology f 4 to f 4 Develop f4and f4 Enhance f4 Functional f4 Competencies
3. f 4 C
LO f41.2, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA 9. f 4 A
f4FC: f 4 Leverage f4 Technology f4 to f 4 Develop f4and f4 Enhance f4 Functional
LO f41.3, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA
f4 Competencies
f4FC: f 4 Leverage f4 Technology f 4 to f4 Develop f4and f4 Enhance f4 Functional
f4 Competencies
4. f 4 B
LO f41 f42, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA 10.D
f4FC: f 4 Leverage f4 Technology f4 to f 4 Develop f4 and f4 Enhance f4 Functional
LO f41.3, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA f4FC:
f4 Competencies
f 4 Leverage f4 Technology f 4 to f4 Develop f4 and f4 Enhance f4 Functional f 4 Competencies
5. f 4 B 11.B
LO f41.2, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA
f4FC: f 4 Leverage f4 Technology f4 to f 4 Develop f4 and f4 Enhance f4 Functional
f4 Competencies
6. f 4 f 4 C
https://www.stuvia.com/user/Prose
1-1
, LO f41.3, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA
f4FC: f 4 Leverage f4 Technology f 4 to f4 Develop f4and f4 Enhance f4 Functional
14.A
f4 Competencies
LO f41.4, f4BT: f4C, f4Difficulty: f4Medium, f4TOT: f43 f4min, f4AACSB: f4Analytic, f4AICPA f4FC:
f 4 Leverage f4 Technology f 4 to f 4 Develop f4and f4 Enhance f4 Functional f4 Competencies
12.A
LO f41.4, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA
15.B
f4FC: f 4 Leverage f4 Technology f 4 to f4 Develop f4and f4 Enhance f4 Functional
LO f41.4, f4BT: f4C, f4Difficulty: f4Medium, f4TOT: f43 f4min, f4AACSB: f4Analytic, f4AICPA f4FC:
f 4 Leverage f4 Technology f 4 to f 4 Develop f4 and f4 Enhance f4 Functional f4 Competencies
f4 Competencies
13.D
LO f41.4, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f42 f4min, f4AACSB: f4Knowledge, f4AICPA
f4FC: f 4 Leverage f4 Technology f 4 to f4 Develop f4and f4 Enhance f4 Functional
f4 Competencies
ANSWERS TO REVIEW QUESTIONS f4 f4 f4
1. Both the CPA exam and the CMA exam have added data analytic content to their exams. This is in
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response to what new professionals need to know as they enter the accounting profession. The
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CPA Exam Evolution is a strong indication of how the accounting profession is changing. The new CPA
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exam will have more technology and data analytics questions in the Core exam, as well as the
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Discipline exams.
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LO f41.1, f4BT: f4K, f4Difficulty: f4Easy,f4TOT: f46f4min, f4AACSB: f4Knowledge, f4AICPA f4FC: f4Leverage f4Technology f4to f4Develop f4and f4Enhance f4Functional f4Competencies
2.
Changes Accounting Practice Area f4 f4
1. Ability to use entire data sets to identify
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exceptions, anomalies, and outliers
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2. Automation of manual processes
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3. Automation of journal entries
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4. Risk identification
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5. Forecasting
f4 ANS: b. Financial accounting, c. Managerial
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accounting
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6. Compliance reporting
f4 f4 ANS: d. Tax accounting
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LO f41.1, f4BT: f4C,f4Difficulty: f4Medium, f4TOT: f48 f4min, f4AACSB: f4Analytic, f4AICPA f4FC: f4Leverage f4Technology f4to f4Develop f4and f4Enhance f4Functional f4Competencies
3. Data are raw facts and figures. Technology helps covert that data into information. Information is
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the knowledge gained from analyzing the data.
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LO f41.1, f4BT: f4C,f4Difficulty: f4Medium, f4TOT: f46 f4min, f4AACSB: f4Analytic, f4AICPA f4FC: f4Leverage f4Technology f4to f4Develop f4and f4Enhance f4Functional f4Competencies
4.
Purpose Method
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, 1. Understanding what is happening currently
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and what has happened in the past.
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2. Understanding what should happen to meet
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our goals and objectives.
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3. Understanding what might happen in the
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future.
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4. Understanding why something happened.
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LO f41.2, f4BT: f4C,f4Difficulty: f4Medium, f4TOT: f46 f4min, f4AACSB: f4Analytic, f4AICPA f4FC: f4Leverage f4Technology f4to f4Develop f4and f4Enhance f4Functional f4Competencies
5. The first step is to identify the motivation for the analysis. The motivation for a project is the why
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the analysis is being performed. It is important to understand the reason for the analysis before
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beginning the analysis.
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The second step is to set an objective. In other words, “What is the goal of the analysis?” This step will
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help articulate the goal and specific questions that will be analyzed.
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The third step is to develop a strategy. In this step, we determine the data and analysis methods
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necessary to achieve the project’s goal.
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LO f41.2, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f48 f4min, f4AACSB: f4Knowledge, f4AICPA f4FC: f4Leverage f4Technology f4to f4Develop f4and f4Enhance f4Functional f4Competencies
6. Extracting is the process in which data is retrieved from a source. This could involve downloading
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an Excel file or extracting data from a database or a data warehouse.
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Transforming the data occurs when data is cleaned, restructured, and/or integrated prior to using it for
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analysis.
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Loading data is the process of importing transformed data into the software used to perform analyses.
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LO f41.2, f4BT: f4K, f4Difficulty: f4Easy, f4TOT: f48 f4min, f4AACSB: f4Knowledge, f4AICPA f4FC: f4Leverage f4Technology f4to f4Develop f4and f4Enhance f4Functional f4Competencies
7.
Example Data Analysis Process Stage
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1. Develop a model to calculate contribution
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margin.
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2. Get data from a database.
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3. Upload data into analysis software.
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4. Determine the objective of the analysis.
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5. Create a forecast of net income.
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6. Identify the data needed for analysis.
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7. Identify relationships within the data.
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8. Create a visualization to show the results of
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the analyses.
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9. Identify sales patterns.
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