TEST BANK for Data Analytics for Accounting, 3rd Edition By Vernon Richardson, Ryan Teeter and Katie by welldoneassistant

CHAPTER 1 TRUE/FALSE - Write 'T' if the statement is true and 'F' if the statement is false. 1) Data analytics is the process of evaluating data with the purpose of drawing conclusions to address business questions. ⊚ true ⊚ false

The process of data analytics aims to transform raw information into data to create value. ⊚ true ⊚ false

3) Data analytics has the potential to transform the manner in which companies run their businesses, however it is not practical in the near future. ⊚ true ⊚ false

4) Auditors can use social media to hear what customers are saying about a company and compare this to inventory obsolescence and other estimates. ⊚ true ⊚ false

5) Data analytics allows auditors to glean insights that are beneficial to the client, without breeching independence. ⊚ true ⊚ false

6) The predictive analytics is an important aspect of data analytics for auditors, but is not applicable for tax accountants. ⊚ true ⊚ false

The I in IMPACT Cycle represents Identify the Question.

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⊚ ⊚

true false

The M in IMPACT Cycle represents Master the Data. ⊚ true ⊚ false

The P in IMPACT Cycle represents Predict the Results. ⊚ true ⊚ false

10)

The A in IMPACT Cycle represents Analyze the Data. ⊚ true ⊚ false

11)

The C in IMPACT Cycle represents Continuously Track. ⊚ true ⊚ false

12)

The T in IMPACT Cycle represents Track Outcomes. ⊚ true ⊚ false

13) The IMPACT cycle is iterative, as insights are gained, outcomes are tracked, and new questions are identified. ⊚ true ⊚ false

14) Data analysis through data manipulation is performing basic analysis to understand the quality of the underlying data and its ability to address the business question. ⊚ true ⊚ false

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15)

To be proficient in data analysis, accountants need to become data scientists. ⊚ true ⊚ false

16) By developing an analytics mindset, accountants will be able to recognize when and how data analytics can address business questions. ⊚ true ⊚ false

17) While it is important for accountants to clearly articulate the business problem, drawing appropriate conclusions, based on the data, should be left to statisticians. ⊚ true ⊚ false

18) Analytic-minded accountants should report results of analysis in an accessible way to each varied decision maker and their specific needs. ⊚ true ⊚ false

MULTIPLE CHOICE - Choose the one alternative that best completes the statement or answers the question. 19) With a goal to give organizations the information they need to make sound and timely business decisions, data analytics often involves all of the following except: A) technologies. B) statistics. C) strategies. D) databases.

20) Patterns discovered from __________blank enable businesses to identify opportunities and risks and better plan for __________blank.

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A) past archives; the future B) current data; the future C) current data; today D) past archives; today

21)

Which of the following best describes the goal of descriptive data analysis:

A) recognize what is meant by data quality, be it completeness, reliability or validity B) perform basic analysis to understand the quality of the underlying data and its ability to address the business question C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows enhanced analysis D) comprehend the process needed to clean and prepare the data before analysis

22)

Which of the following Microsoft software tool specializes in data joining? A) Excel B) Power Query C) Power BI D) Power Automate

23)

Which of the following Microsoft software tools specializes in creating dashboards? A) Excel B) Power Query C) Power BI D) Power Automate

24)

Which of the following Tableau software tools specializes in data transformation?

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A) Tableau Desktop B) Tableau Prep Builder C) Tableau Public D) Tableau Visualize

25)

Which of the following Tableau software tools specializes in creating dashboards? A) Tableau Desktop B) Tableau Prep Builder C) Tableau Public D) Tableau Visualize

26)

Which of the following best describes the goal of data quality:

27)

Which of the following best describes the goal of data manipulation:

28)

Which of the following best describes the goal of data scrubbing and data preparation:

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A) recognize what is meant by data quality, be it completeness, reliability or validity B) perform basic analysis to understand the quality of the underlying data and its ability to address the business question C) demonstrate ability to sort, rearrange, merge and reconfigure data in a manner that allows enhanced analysis D) comprehend the process needed to clean and prepare the data before analysis

29)

Which of the following best describes the goal of developing an analytics mindset:

A) recognize when and how data analytics can address business questions B) perform basic analysis to understand the quality of the underlying data and its ability to address the business question C) recognize what is meant by data quality, be it completeness, reliability or validity D) comprehend the process needed to clean and prepare the data before analysis

30)

Which of the following best describes the goal of data visualization and data reporting:

A) recognize when and how data analytics can address business questions B) perform basic analysis to understand the quality of the underlying data and its ability to address the business question C) recognize what is meant by data quality, be it completeness, reliability or validity D) report results of analysis in an accessible way to each varied decision maker and their specific needs

31) Which of the following best describes the goal of defining and addressing problems through statistical data analysis: A) recognize what is meant by data quality, be it completeness, reliability or validity B) perform basic analysis to understand the quality of the underlying data and its ability to address the business question C) demonstrate ability to sort, rearrange, merge and reconfigure data in a manner that allows enhanced analysis D) identify and implement an approach that will use statistical data analysis to draw conclusions and make recommendations on a timely basis

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32) While accountants don't need to become data scientists, they must know how to do the following except: A) Clearly articulate the business problem the company is facing B) Communicate with the data scientists about specific data needs and understand the underlying quality of the data C) Build a data repository D) Comprehend the process needed to clean and prepare the data before analysis

33) Data analytics professionals estimate that they spend between __________blank of their time cleaning data so it can be analyzed.

A) 50 percent and 90 percent B) 10 percent and 20 percent C) 20 percent and 50 percent D) 70 percent and 95 percent

34) Which approach to data analytics attempts to estimate or predict, for each unit, the numerical value of some variable using some type of statistical model? A) Similarity matching. B) Classification. C) Data reduction. D) Regression.

35) Which approach to data analytics attempts to characterize the typical behavior of an individual, group or population by generating summary statistics about the data? A) Similarity matching. B) Profiling. C) Data reduction. D) Regression.

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36) Since some transactions need more attention than others, the data reduction approach would arguably be most important for the __________blank function.

A) audit B) tax. C) management accounting. D) Regression.

37) Which approach to data analytics attempts to reduce the amount of information that needs to be considered to focus on the most critical items? A) Similarity matching. B) Profiling. C) Data reduction. D) Regression.

38)

Which of the following best describes the classification approach to data analytics?

A) An attempt to assign each unit (or individual) in a population into a few categories. B) An attempt to identify similar individuals based on data known about them. C) An attempt to divide individuals into groups in a useful or meaningful way. D) An attempt to discover associations between individuals based on transactions involving them.

39)

Which of the following best describes the clustering approach to data analytics?

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40)

Which of the following best describes the similarity matching approach to data analytics?

41)

Which of the following best describes the regression approach to data analytics?

A) An attempt to estimate or predict, for each unit, the numerical value of some variable using some type of statistical model. B) An attempt to predict a relationship between two data items. C) An attempt to divide individuals into groups in a useful or meaningful way. D) An attempt to discover associations between individuals based on transactions involving them.

42) Which of the following best describes the co-occurrence grouping approach to data analytics? A) An attempt to characterize the typical behavior of an individual, group or population by generating summary statistics about the data. B) An attempt to predict a relationship between two data items. C) An attempt to reduce the amount of information that needs to be considered to focus on the most critical items. D) An attempt to discover associations between individuals based on transactions involving them.

43)

Which of the following best describes the link prediction approach to data analytics?

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A) An attempt to characterize the typical behavior of an individual, group or population by generating summary statistics about the data. B) An attempt to predict a relationship between two data items. C) An attempt to reduce the amount of information that needs to be considered to focus on the most critical items. D) An attempt to discover associations between individuals based on transactions involving them.

44)

Which of the following best describes the profiling approach to data analytics?

45)

Which of the following best describes the data reduction approach to data analytics?

46) Which approach to data analytics attempts to discover associations between individuals based on transactions involving them?

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A) Similarity matching. B) Clustering. C) Co-occurrence grouping. D) Link prediction.

47) Which approach to data analytics attempts to identify similar individuals based on data known about them? A) Similarity matching. B) Clustering. C) Co-occurrence grouping. D) Link prediction.

48) Which approach to data analytics attempts to predict a relationship between two data items? A) Similarity matching. B) Clustering. C) Co-occurrence grouping. D) Link prediction.

49) Which approach to data analytics attempts to divide individuals into groups in a useful or meaningful way? A) Similarity matching. B) Clustering. C) Co-occurrence grouping. D) Link prediction.

50)

The IMPACT cycle includes all the following processes except:

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A) Identify the questions. B) Address and refine results. C) Track outcomes. D) Predict the results.

51)

One of the most important aspects of data analytics that impacts tax is: A) predictive analytics. B) co-occurrence grouping. C) similarity matching. D) data quality.

52)

If we are predicting which companies go bankrupt, bankruptcy would be the A) dependent variable B) independent variable C) explanatory variable D) classification variable

53) If a bank uses credit risk score to determine who will receive a loan, the credit risk score would be considered the: A) dependent variable B) independent variable C) response variable D) classification variable

54) If a bank uses credit risk score to determine who will receive a loan, the variable predicting who will receive a loan would be considered the:

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A) dependent variable B) independent variable C) determinant variable D) classification variable

55)

The 4V’s of Big Data include all but the following: A) volatility B) variety C) velocity D) veracity

56) A recent study from McKinsey Global Institute estimates that Data Analytics could generate up to $2 __________blank in value. A) billion B) trillion C) million D) thousand

57) The PwC’s 6th Annual Digital IQ survey of more than 1,400 leaders from digital business, the area of investment that tops CEOs’ list of priorities is: A) information technology B) capital expenditures including hardware and software C) accounting data analytics D) business analytics

58) According to PwC’s 18th Annual Global CEO survey, __________blank percent of chief executive officers put a high value on data analytics.

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A) 95 B) 86 C) 55 D) 35

59) According to the text, as the debt-to-income ratio increases, there is __________blank chance of a loan getting rejected by the bank. A) a greater B) a lesser C) no effect on the

60) According to the text, as the length of employment increases, there is __________blank chance of a loan getting rejected by the bank. A) a greater B) a lesser C) no effect on the

61) According to the text, as the credit score increases, there is __________blank chance of a loan getting rejected by the bank. A) a greater B) a lesser C) no effect on the

62)

In the LendingClub dataset, a credit score is synonymous with:

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A) a debt score. B) a risk score. C) a credit card score. D) a premium score.

ESSAY. Write your answer in the space provided or on a separate sheet of paper. 63) List and describe the eight (8) different approaches to data analytics.

64) List and explain four (4) of the seven (7) data analytic skills needed by analytic-minded accountants:

65) As more and more data are available, some would argue that the role of accounting is changing. While accountants don't need to become data scientists, they must develop a base level skill set. Whether they are the Director of Tax for Hewlett Packard or their external auditor, which basic skills are needed by an analytic-minded accountant?

66) What is the regression approach? How might the regression approach be used in auditing?

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67) Assume that you have just started a new job as a credit manager for a Fortune 500 company. Using all steps in the IMPACT Cycle, provide examples of tasks that would be performed as part of each step and state the information/data you would need to make a decision if a customer is credit worthy.

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Answer Key Test name: Chap 01_3e_Richardson 1) TRUE 2) FALSE 3) FALSE 4) TRUE 5) TRUE 6) FALSE 7) TRUE 8) TRUE 9) FALSE 10) FALSE 11) FALSE 12) TRUE 13) TRUE 14) FALSE 15) FALSE 16) TRUE 17) FALSE 18) TRUE 19) C 20) A 21) B 22) B 23) C 24) B 25) A 26) A Version 1

27) C 28) D 29) A 30) D 31) D 32) C 33) A 34) D 35) B 36) A 37) C 38) A 39) C 40) B 41) A 42) D 43) B 44) A 45) C 46) C 47) A 48) D 49) B 50) D 51) A 52) A 53) B 54) A 55) A 56) B Version 1

57) D 58) B 59) A 60) B 61) B 62) B 63)Answers may vary slightly! ● Classification — An attempt to assign each unit (or individual) in a population into a few categories. ● Regression — An attempt to estimate or predict, for each unit, the numerical value of some variable using some type of statistical model. ● Similarity matching — An attempt to identify similar individuals based on data known about them. ● Clustering — An attempt to divide individuals (like customers) into groups (or clusters) in a useful or meaningful way. ● Co-occurrence grouping — An attempt to discover associations between individuals based on transactions involving them. ● Profiling — An attempt to characterize the "typical" behavior of an individual, group or population by generating summary statistics about the data (including mean, standard deviations, etc.). ● Link prediction — An attempt to predict a relationship between two data items. ● Data reduction — A data approach that attempts to reduce the amount of information that needs to be considered to focus on the most critical items (i.e., highest cost, highest risk, largest IMPACT, etc.).

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64)Answers will vary but should include some of these items. ● Developing an analytics mindset — recognize when and how data analytics can address business questions. ● Data scrubbing and data preparation — comprehend the process needed to clean and prepare the data before analysis. ● Data quality — recognize what is meant by data quality, be it completeness, reliability or validity. ● Descriptive data analysis — perform basic analysis to understand the quality of the underlying data and its ability to address the business question. ● Data analysis through data manipulation — demonstrate ability to sort, rearrange, merge and reconfigure data in a manner that allows enhanced analysis. ● Defining and addressing problems through statistical data analysis — identify and implement an approach that will use statistical data analysis to draw conclusions and make recommendations on a timely basis. ● Data visualization and data reporting — report results of analysis in an accessible way to each varied decision maker and their specific needs. 65)Answers will vary! ● Clearly articulate the business problem the company is facing, ● Communicate with the data scientists about specific data needs and understand the underlying quality of the data. ● Draw appropriate conclusions to the business problem based on the data and make recommendations on a timely basis, and ● Present their results to individual members of management (CEOs, audit managers, etc.) in an accessible manner to each member.

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66)Answers will vary! Regression is an attempt to estimate or predict, for each unit, the numerical value of some variable using some type of statistical model. Given a balance of total accounts receivable held by a client, auditors can use a regression analysis to estimate the appropriate level of allowance for doubtful accounts for bad debts. 67)Answers will vary! A potential answer might include: Process: Example or Information need: Identify the Question Who is the customer?

What is the credit amount requested?

What are the terms of payment?

How is their financial performance, relative to their competitors?

Master the Data

What is their:

● Liquidity ratio,

● Effectiveness or turnover ratios,

● Financial leverage ratios,

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● Profitability ratios,

● Ratios of debt service.

Perform Test Plan

Possible approaches

● Regression

● Profiling

● Data reduction

Address and Refine Results

● Examine correlations

● Request additional data

● Discuss with colleagues

● Rerun analysis

Communicate Insights

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Provide answer (yes/no) to customer. If yes, provide amount of credit limit and payment

terms.

Track Outcomes

● Monitor customer aging and payment trends

● Revisit as necessary

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CHAPTER 2 TRUE/FALSE - Write 'T' if the statement is true and 'F' if the statement is false. 1) Mastering the data requires a firm understanding of what data is available to you and where it is stored, as well as being skilled in the process of extracting, transforming, and loading (ETL). ⊚ true ⊚ false

2) A flat file is a means of storing data in one place, such as in an Excel spreadsheet, as opposed to storing the data in multiple tables, such as in a relational database. ⊚ true ⊚ false

3) A foreign key is an attribute that is required to exist in each table of a relational database and serves as the unique identifier for each record in a table. ⊚ true ⊚ false

4) A primary key is an attribute that is required to exist in each table of a relational database and serves as the unique identifier for each record in a table. ⊚ true ⊚ false

5) A foreign key is an attribute that exists in relational databases in order to carry out the relationship between two tables. ⊚ true ⊚ false

6) A composite primary key is made up of the three or more primary keys in the tables that it is linking. ⊚ true ⊚ false

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7) Descriptive attributes are attributes that exist in relational databases that are neither primary nor foreign keys. ⊚ true ⊚ false

8) Once you have extracted the data of interest, it will need to be validated for completeness and existence. ⊚ true ⊚ false

The M in IMPACT Cycle represents Manipulating the Data. ⊚ true ⊚ false

10) In order to obtain the right data, it is important to have a firm grasp of what data is available and how it is stored. ⊚ true ⊚ false

11)

Data normalization can reduce data redundancy and improve data integrity. ⊚ true ⊚ false

12)

Much like the IMPACT cycle, requesting data is often an iterative process. ⊚ true ⊚ false

13)

Unlike the IMPACT cycle, requesting data is not an iterative process. ⊚ true ⊚ false

14) If the extraction and transformation steps have been done correctly, the loading part of the ETL process should be the simplest step.

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⊚ ⊚

true false

15) After obtaining the data and determining the purpose and scope of the data request, the next step is to validate the data. ⊚ true ⊚ false

16)

Formatting negative numbers is an example of cleaning the data. ⊚ true ⊚ false

17)

A template can make communication easier between data requestor and provider. ⊚ true ⊚ false

MULTIPLE CHOICE - Choose the one alternative that best completes the statement or answers the question. 18) Mastering the data can also be described via the ETL process. The ETL process stands for: A) Extract, total, and load data. B) Extract, transform, and load data. C) Enter, transform, and load data. D) Enter, total, and load data.

19) All of the following are Audit Data Standards (ADS) developed by the American Institute of Certified Public Accountants except: A) Investments subledger standards B) General Ledger standards C) Procure-to-Pay subledger standards D) Order-to-Cash subledger standards

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20) When using [EmployeeID] as the unique identifier of the Employee table, [EmployeeID] is an example of which of the following: A) Foreign key B) Composite key C) Primary key D) Key attribute

21)

What would be the best primary key for the LendingClub rejected loan dataset? A) Loan application number B) Zip code C) Customer number D) Loan number

22)

The objective of data extraction is: A) To validate the data for completeness and integrity B) To load the data into the appropriate tool for analysis C) To identify and obtain the data from the appropriate source D) To identify which approach to data analytics should be used

23)

The objective of data transformation is: A) To validate the data for completeness and integrity B) To load the data into the appropriate tool for analysis C) To identify and obtain the data from the appropriate source D) To identify which approach to data analytics should be used

24)

The objective of loading data is:

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A) To validate the data for completeness and integrity B) To load the data into the appropriate tool for analysis C) To identify and obtain the data from the appropriate source D) To identify which approach to data analytics should be used

25)

All of the following are included in the five steps of the ETL process except: A) Determine the purpose and scope of the data request B) Obtain the data C) Validate the data for completeness and integrity D) Scrub the data

26) Which of the following best exemplifies a way that data will need to be cleaned after extraction and validation? A) Remove headings and subtotals B) Validate date/time fields C) Remove trailing zeroes D) Compare string limits for text fields

27)

Removing headings or subtotals from data is an example of which of the following? A) Validating the data for completeness B) Validating the data for integrity C) Cleaning the data D) Obtaining the data

28)

Correcting inconsistencies across data is an example of which of the following?

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A) Validating the data for completeness B) Validating the data for integrity C) Cleaning the data D) Obtaining the data

29)

Formatting negative numbers in the data is an example of which of the following? A) Validating the Data for Completeness B) Validating the Data for Integrity C) Cleaning the Data D) Obtaining the Data

30) Removing leading zeroes and non-printable characters from the data is an example of which of the following? A) Validating the data for completeness B) Validating the data for integrity C) Cleaning the data D) Obtaining the data

31) Comparing descriptive statistics for numeric fields within the data is an example of which of the following? A) Validating the data for completeness B) Validating the data for integrity C) Cleaning the data D) Obtaining the data

32) Comparing the number of records within the data is an example of which of the following?

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A) Validating the data for completeness B) Validating the data for integrity C) Cleaning the data D) Obtaining the data

33) Which of the following questions are NOT suggested by the Institute of Business Ethics to allow a business to create value from data use and analysis, and still protect the privacy of stakeholders? A) How does the company use data, and to what extent is it integrated into firm strategy? B) Does the company send a privacy notice to individuals when their personal data is collected? C) Is the data kept in a secure location preventing access from unauthorized users? D) Does the company have the appropriate tools to mitigate the risks of data misuse?

34) Which of the following questions are NOT suggested by the Institute of Business Ethics to allow a business to create value from data use and analysis, and still protect the privacy of stakeholders? A) Does our company conduct appropriate due diligence when sharing with or acquiring data from third parties? B) How does the company use data, and to what extent is it integrated into firm strategy? C) Does the company send a privacy notice to individuals when their personal data is collected? D) Does the company require analysts to sign a confidentiality agreement the information found in the data?

35)

Which of the following best describes the purpose of a primary key? A) To uniquely identify each row in a table. B) To create the relationship between two tables. C) To provide business information, but are not required to build a database. D) To support business processes across the organization.

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36)

Which of the following best describes the purpose of a non-key attribute? A) To ensure that each row in the table is unique B) To create the relationship between two tables C) To provide business information D) To support business processes across the organization

37)

Which of the following best describes the purpose of relational databases? A) To ensure that business rules are enforced B) To increase information redundancy in the organization C) To provide business information to data analysts D) To support business processes across the organization

38)

Which of the following best describes the purpose of a foreign key? A) To ensure that each row in the table is unique B) To create the relationship between two tables C) To provide business information D) To support business processes across the organization

39)

A data dictionary is paramount in helping data analysts do which of the following? A) Maintain databases. B) Identify the data they need to use. C) Communicating insights. D) Track outcomes.

40) A data dictionary is paramount in helping database administrators do which of the following?

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A) Maintain databases. B) Identify the data they need to use. C) Communicating insights. D) Track outcomes.

41) At which step of the ETL process should you try to answer the question "What tools will be used to perform data analytic tests or procedures and why?" A) Step 1: Determine the purpose and scope of the data request. B) Step 2: Obtain the data. C) Step 3 or 4: Transformation. D) Step 5: Loading the data for data analysis.

42) At which step of the ETL process should you try to answer the question "What other information will impact the nature, timing and extent of the data analysis?" A) Step 1: Determine the purpose and scope of the data request. B) Step 2: Obtain the data. C) Step 3 or 4: Transformation. D) Step 5: Loading the data for data analysis.

43) At which step of the ETL process should you try to answer the question "What business problem will the data address?" A) Step 1: Determine the purpose and scope of the data request. B) Step 2: Obtain the data. C) Step 3 or 4: Transformation. D) Step 5: Loading the data for data analysis.

44) At which step of the ETL process should you try to answer the question "Where are the data located in the financial or other related systems?"

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A) Step 1: Determine the purpose and scope of the data request. B) Step 2: Obtain the data. C) Step 3 or 4: Transformation. D) Step 5: Loading the data for data analysis.

45) When obtaining the data yourself, you should do all of the following before you begin except: A) Identify the tables that contain the information you need. B) Identify which attributes specifically hold the information you need in each table. C) Identify how those tables are related to each other. D) Identify any errors or issues from the extraction.

46) There are a variety of methods that you could take to retrieve the data, including SQL. What does SQL stand for? A) Systems Query Language. B) Systems Question Language. C) Structured Question Language. D) Structured Query Language.

47)

All of the following are benefits of using a normalized relational database except: A) Completeness. B) No redundancy. C) Business rules are enforced. D) Data is stored in one place.

48)

Which of the following is most likely to be the primary key in an Employee table?

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A) Employee ID B) Employee Social Security Number C) Employee Name D) Employee Type

49) Comparing the number of records that were extracted to the number of records in the source database is an example of which ETL step. A) Validating the Data B) Obtaining the Data C) Cleaning the Data D) Loading the Data for Analysis

50) Which of the following describes a means of maintaining all of your data in one place, instead of across different related tables? A) Flat File B) Microsoft Access C) SQL lite D) Microsoft SQL Server

51)

Which of the following is NOT true regarding Primary Keys?

A) The purpose of the primary key is to uniquely identify each column in a table. B) A primary key is typically a sequential number instead of something truly descriptive about each record. C) Primary keys are required in each table in a relational database. D) Primary keys do not provide meaningful business information.

52) Relational databases help to reduce redundant data. Which of the following is NOT a reason to reduce redundant data?

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A) It takes up unnecessary space B) It is expensive C) It increases the risk of data-entry errors D) It is easier to perform analysis in spreadsheets

53)

What is the purpose of the Audit Data Standards? A) To provide a guide to standardize audit data requests B) To increase the cost of audits C) To help auditors learn SQL code D) To create standardized data storage systems

54) There are many times when using SQL is the best option for extracting data, but sometimes it is not preferred. Which of the following is an example of when SQL would NOT be a preferred method of data extraction? A) When the data is already stored in Excel B) When the data is stored across different tables in a relational database C) When the data in the table you wish to analyze is too large for Excel’s resources D) When you wish to extract precise attributes and records that fit your criteria

55)

What is one of Excel’s tools for joining data from two separate spreadsheets? A) SUMIF B) VLOOKUP C) SQL D) DATAREQUEST

56)

What is one of Excel’s tools is roughly equivalent to the VLOOKUP function?

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A) INDEX/MATCH B) SELECT C) LINK D) LINKUP

57)

What follows the ETL process of “Validating the Data”? A) Loading the Data for Analysis B) Obtain the data C) Determining the scope of the data request D) Cleaning the data

58)

What follows the ETL process of “Obtaining the Data”? A) Loading the Data for Analysis B) Obtain the data C) Validating the data for completeness and integrity D) Cleaning the data

ESSAY. Write your answer in the space provided or on a separate sheet of paper. 59) Chapter 2 describes the various ways in which data can be stored for differing purposes. Describe the two ways data can be organized and the purpose for each organizational structure.

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60) Taylor is a new staff accountant for a fortune 100 company. After hearing that she just successfully completed an Accounting Data Analytics course, her boss said, "Get me a listing of all our deadbeat customer, so I can cut off their credit." After asking clarifying questions, Taylor was able to determine that root request was "Which customer, with a credit limit over $10,000, have more than $5,000 outstanding for more than 90 days at the prior quarter's end?" Using the ETL Techniques, briefly describe the process Taylor will have to complete to answer her boss' question. (Assume that Taylor does not have direct access to the data, rather the data will be exported into an Excel file, and she will complete the analysis with an Excel Pivot Table.)

61)

Define and give 1 example of a primary key, a foreign key, and non-key attribute.

62) Assume that you will be up for a promotion next month and you'd like to analyze a database that was recently assigned to you to show off your data analytic skills. After identifying the goal of your data analysis, using the first step of the IMPACT cycle, what steps would you take if you have direct access to the database?

63) Assume that you have just completed the extraction process on a data set. As you begin validating the data for completeness and integrity, you notice an error. Describe the steps you might take to determine the source of an error.

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Answer Key Test name: Chap 02_3e_Richardson 1) TRUE 2) TRUE 3) FALSE 4) TRUE 5) TRUE 6) FALSE 7) TRUE 8) FALSE 9) FALSE 10) TRUE 11) TRUE 12) TRUE 13) FALSE 14) TRUE 15) TRUE 16) TRUE 17) TRUE 18) B 19) A 20) C 21) A 22) C 23) A 24) B 25) D 26) A Version 1

27) C 28) C 29) C 30) C 31) A 32) A 33) C 34) D 35) A 36) C 37) D 38) B 39) B 40) A 41) B 42) A 43) A 44) B 45) D 46) D 47) D 48) A 49) A 50) A 51) A 52) D 53) A 54) A 55) B 56) A Version 1

A) Descriptive analytics B) Diagnostic analytics C) Predictive analytics D) Prescriptive analytics

37) Which type of tax analytics summarizing transactions by jurisdiction or category to more accurately calculate tax liability? A) Descriptive analytics B) Diagnostic analytics C) Predictive analytics D) Prescriptive analytics

38) Which type of tax analytics provide insight which might help identify items of interest, such as high tax areas or excluded transactions? A) Descriptive analytics B) Diagnostic analytics C) Predictive analytics D) Prescriptive analytics

39) Which type of tax analytics uses ancillary data, including growth rates, trends, and other identified patterns, aids in the usefulness of regression and what-if analyses? A) Descriptive analytics B) Diagnostic analytics C) Predictive analytics D) Prescriptive analytics

40)

Which type of tax analysis tests the impact of various input data on an expected output?

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A) What-if Scenario Analysis B) Goal Seek Analysis C) Cash Flow Analysis D) What-if Case Analysis

41) To plan for the impact on taxes of the recent change in accounting for research and experimental expenditures, analysts may use which of the following types of prescriptive analytics? A) What-if Scenario Analysis B) Goal Seek Analysis C) Regression Analysis D) What-if Case Analysis

42) Determining the appropriate structure of a merger and/or acquisition transaction that would give the greatest tax advantage would be an example of: A) descriptive analytics. B) diagnostic analytics. C) predictive analytics. D) prescriptive analytics.

43)

The effective tax rate over time would be an example of which kind of KPI? A) Tax cost B) Tax risk C) Tax efficiency and effectiveness D) Tax sustainability

44) The amount of time spent on compliance versus strategic activities would be an example of which kind of KPI?

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