Question: Go to finance.yahoo.com and type

> What are some patterns that could be found using diagnostic analysis? Between which types of variables?

> What does a Z-score greater than three (or minus three) suggest? How is that useful in finding extreme values? What type of analysis should we do when we find extreme or outlier values?

> One of the benefits of Data Analytics is the ability to see and test the full population. In that case, why is sampling (even monetary sampling) still used, and how is it useful?

> One type of descriptive analytics is age analysis. Why are auditors particularly interested in the aging of accounts receivable and accounts payable? How does this analysis help evaluate management judgment on collectability of receivables and potential

> Implementing continuous auditing procedures is similar to automating an audit plan with the additional step of scheduling the automated procedures to match the timing and frequency of the data being evaluated and the notification to the auditor when exce

> What approach should a company make if its continuous audit system has too many alarms that are false positives? How would that approach change if there are too many missed abnormal events (such as false negatives)?

> Simple to complex Data Analytics can be applied to a client’s data during the planning stage of the audit to identify which areas the auditor should focus on. Which types of techniques or tests might be used in this stage?

> Who developed the audit data standards? In your opinion, why is it the right group to develop and maintain them rather than, say, the Big 4 firms or a small practitioner?

> Consider Exhibit 5-3. Looking at the audit data standards order-to-cash process, what function is there for the AR Adjustments transaction table—that is, adjustments to the Accounts Receivable? Why is this an audit data standard, and why is it important

> What are the advantages of the use of homogeneous systems? Would a merger target be more attractive if it used a similar financial reporting system as the potential parent company?

> Regarding the data request form, why do you think it is important to the database administrator to know the purpose of the request? What would be the importance of the “To be used in” and “intended audience” fields?

> In your opinion, is the primary reason that analysts use inappropriate scales for their charts primarily due to an error related to naiveté (or ineffective training), or are the inappropriate scales used so the analyst can sway the audience one way or th

> Datavizcatalogue.com lists seven types of maps in its listing of charts. Which one would you use to assess geographic customer concentration by number? How could you show if some customers buy more than other customers on such a map? Would you use the sa

> The Big 4 accounting firms (Deloitte, EY, KPMG, and PwC) dominate the audit and tax market in the United States. What chart would you use to show which accounting firm dominates in each state in terms of audit revenues? Any there other interesting ways y

> According to Exhibit 4-8, which is the best chart for static composition of a data item of the Accounts Receivable balance at the end of the year? Which is best for showing a change in composition of Accounts Receivable over two or more periods?

> According to Exhibit 4-8, which is the best chart for comparisons of earnings per share over many periods? How about for only a few periods?

> Evaluate the use of multiple colors in the graphic associated with the opening vignette regarding the 2016 presidential election. Would you consider its use effective or ineffective? Why? Can you think of a better way to communicate the extent to which p

> Why was the graphic associated with the opening vignette regarding the 2016 presidential election an effective way to communicate the voter outcome for 50 states? What else could have been used to communicate this, and would it have been more or less eff

> Name three accounts that it would be appropriate and interesting to apply Benford’s Law in auditing those accounts? Why would an auditor choose those three accounts? When would a departure from Benford’s Law encourage the auditor to investigate further

> How could XBRL be used by an investor to do an analysis of the industry’s inventory turnover?

> Why would the use of data reduction be useful to highlight related party transactions (e.g., CEO has her own separate company that the main company does business with)?

> In the ETL process, when an analyst is completing the data request form, there are a number of fields that the analyst is required to complete. Why do you think it is important for the analyst to indicate the frequency of the report? How do you think tha

> How might clustering be used to explain customers that owe us money (accounts receivable)?

> An auditor is trying to figure out if the goodwill its client recognized when it purchased a factory has become impaired. What characteristics might be used to help establish a model predicting goodwill impairment?

> An auditor is trying to figure out if the inventory at an electronics store chain is obsolete. What characteristics might be used to help establish a model predicting inventory obsolescence?

> Related party transactions involve people who have close ties to an organization, such as board members. Assume an accounting manager decides that fuzzy matching would be a useful technique to find undisclosed related party transactions. What data would

> Use the College Scorecard data to determine if different regions of the country have significantly different costs of attendance (same as Problem 6 above) and fill out a data request form in order to extract the appropriate data. Use the template from th

> Which attributes from the College Scorecard data would you need to determine if different regions of the country have significantly different costs of attendance?

> Which attributes from the College Scorecard data would you need to compare the percentage of students who receive federal loans at universities above and below the median cost of attendance across all institutions (public, private non-profit, or private

> Which attributes from the College Scorecard data would you need to compare completion rate across types of institutions (public, private non-profit, or private for-profit)?

> Which attributes from the College Scorecard data would you need to compare levels of diversity across types of institutions (public, private non-profit, or private for-profit)?

> Which attributes from the College Scorecard data would you need to compare SAT scores across types of institutions (public, private non-profit, or private for-profit)?

> What is included in mastering the data as part of the IMPACT cycle described in the chapter?

> If you were conducting a data analysis in order to compare the percentage of students who receive federal loans at universities above and below the median cost of attendance across all institutions, you would be conducting several steps in your analysis.

> If you were analyzing the levels of diversity across public and private institutions using the College Scorecard data, how would you define diversity in terms of the data provided? Would it be beneficial to combine fields?

> Consider the 2013 declined loan data from Lending Club titled “RejectStatsB2013.” Similar to the analysis done in the chapter, let’s scrub the employment length. Because our analysis requires risk scores, debt-to-income data, and employment length, we ne

> Consider the 2013 declined loan data from LendingClub titled “RejectStatsB2013.” Similar to the analysis done in the chapter, let’s scrub the debt-to-income data. Because our analysis requires risk scores, debt-to-income data, and employment length, we n

> Consider the 2013 declined loan data from LendingClub titled “RejectStatsB2013” from the Connect website. Similar to the analysis done in the chapter, let’s scrub the risk score data. First, because our analysis requires risk scores, debt-to-income data,

> Download the rejected loans dataset of LendingClub data titled “Reject Stats A Ready” from the Connect website and do an Excel PivotTable by state; then figure out the number of rejected applications for each state. Reorder these and make a graph orderin

> 1. Mastering the data can also be described via the ETL process. The ETL process stands for: a. Extract, total, and load data. b. Enter, transform, and load data. c. Extract, transform, and load data. d. Enter, total, and load data. 2. The goal of the ET

> 1. Big Data is often described by the three Vs, or a. Volume, velocity, and variability. b. Volume, velocity, and variety. c. Volume, volatility, and variability. d. Variability, velocity, and variety. 2. Which approach to Data Analytics attempts to assi

> 1. The DuPont analysis of return on equity (ROE) includes all of the following component ratios except: a. Asset turnover. b. Inventory turnover. c. Financial leverage. d. Profit margin. 2. XBRL stands for: a. Extensible Business Reporting Language. b. E

> 1. What would you consider to be Financial Performance KPIs? a. Total Shareholder Return b. Customer Profitability Score c. Market Growth Rate d. Klout Score 2. What would you consider to be an Operational KPI? a. Inventory Shrinkage Rate b. Brand Equity

> In the ETL process, the first step is extracting the data. When you are obtaining the data yourself, what are the steps to identifying the data that you need to extract?

> 1. Which items would be currently out of scope for Data Analytics? a. Direct observation of processes b. Evaluation of time stamps to evaluate workflow c. Evaluation of phantom vendors d. Duplicate payment of invoices 2. What would be the sampling interv

> 1. Under the guidance of the chief audit executive (CAE) or another manager, these individuals build teams to develop and implement analytical techniques to aid all of the following audits except: a. Process efficiency and effectiveness. b. Governance, r

> 1. Gold, silver, and bronze medals would be examples of: a. Nominal data. b. Ordinal data. c. Structured data. d. Test data. 2. In the late 1960s, Ed Altman developed a model to predict if a company was at severe risk of going bankrupt. He called his sta

> 1. Is a set of data used to assess the degree and strength of a predicted relationship. a. Training data b. Unstructured data c. Structured data d. Test data 2. Data that are organized and reside in a fixed field with a record or a file. Such data are

> Can you think of any other settings, besides financial reports, where tagged data might be useful for fast, accurate analysis generally completed by computers? How could it be used in a hospital setting? Or at your university?

> Go to https://xbrl.us/data-rule/dqc_0015-lepr/ and find the XBRL element name for Other NonOperating Income and indicate whether XBRL says that should normally be a debit or credit entry.

> Go to https://xbrl.us/data-rule/dqc_0015-lepr/ and find the XBRL element name for Interest Expense and Sales, General, and Administrative expense.

> Why do audit firms perform analytical procedures to identify risk? Which type of ratios (liquidity, solvency, activity, and profitability ratios) would you use to evaluate the company’s ability to continue as a going concern?

> Would you recommend the Securities and Exchange Commission require the use of sparklines on the face of the financial statements? Why or why not?

> Describe the IMPACT cycle. Why does its order of the processes and its recursive nature make sense?

> Which would you predict would have more positive sentiment in a 10-K, the financial statements or the MD&A (management discussion and analysis) of the financial statements? More positive sentiment in the footnotes or MD&A? Why?

> In which of the four components of a Balanced Scorecard would you put the Walton College’s diversity initiative? Why do you think this is important for a public institution of higher learning?

> If the data underlying your digital dashboard are updated in real time, why would you want to update your digital dashboard in real time? Are there situations when you would not want to update your digital dashboard in real time? Why or why not?

> Why is Customer Retention Rate a great KPI for understanding your Tesla customers?

> For a company like Walmart, how would the Balanced Scorecard help balance the desire to be profitable for its shareholders with continuing to develop organizational capacity to compete with Amazon (and other online retailers)?

> For an accounting firm like PwC, how would the Balanced Scorecard help balance the desire to be profitable for its partners with keeping the focus on its customers?

> Amazon, in the author’s opinion, has cared less about profitability in the short run but has cared about gaining market share. Arguably Amazon gains market share by taking care of the customer. Given the “Suggested 75 KPIs That Every Manager Needs to Kno

> We know that a Balanced Scorecard is comprised of four components: financial (or stewardship), customer (or stakeholder), internal process, and organizational capacity (or learning and growth). What would you include in a dashboard for the internal proce

> We know that a Balanced Scorecard is comprised of four components: financial (or stewardship), customer (or stakeholder), internal process, and organizational capacity (or learning and growth). What would you include in a dashboard for the financial and

> One type of descriptive analytics is simply sorting data. Why is seeing extreme values helpful (minimums, maximums, counts, etc.) in evaluating accuracy and completeness and in potentially finding errors and fraud and the like?

> How might Data Analytics be used in financial reporting? And how might it be used in doing tax planning?

> An example of prescriptive analytics is when an action is recommended based on previously observed actions. For example, an analysis might help determine procedures to follow when new accounts are opened for inactive customers, such as requiring supervi

> Using Table 6-2 as a guide, compare and contrast predictive and prescriptive analytics. How might these be used in an audit? Or a continuous audit?

> When do you believe that Data Analytics will add value to the audit process? How can it most help?

> How do nature, extent, and timing of audit procedures help us identify when to apply Data Analytics to the audit process?

> Why would audit firms prefer to use proprietary workpapers rather than just storing working papers on the cloud?

> Would an auditor view heterogeneous systems as an audit risk? Why or why not?

> Why is it better to extract data from a data warehouse than a production or live system directly?

> How does the systems translator software work? How does it store the merged data into a data warehouse?

> Is it possible for multinational firms to have many different financial reporting systems and ERP packages all in use at the same time?

> Is it possible for a firm to have general journals from a product like JD Edwards actually reconcile to the general ledger in SAP? Why or why not?

> Even though it is preferable to store data in a relational database, storing data across separate tables can make data analysis cumbersome. Describe three reasons why it is worth the trouble to store data in a relational database.

> Why has most innovation in Data Analytics originated more in an internal audit than an external audit? Or if not, why not?

> The text mentions, “If your data analysis project is more declarative than exploratory, it is more likely that you will perform your data visualization to communicate results in Excel.” In your opinion, why is this true?

> Box and whisker plots (or box plots) are particularly adept at showing extreme observations and outliers. In what situations would it be important to communicate these data to a reader? Any particular accounts on the balance sheet or income statement?

> According to Exhibit 4-8, which is the best chart for showing a distribution of a single variable, like height? How about hair color? Major in college?

> Explain Exhibit 4-2 and why these four dimensions are helpful in describing information to be communicated? Exhibit 4-2 lists conceptual and data-driven as being on two ends of the continuum. Does that make sense, or can you think of a better way to orga

> How does fuzzy match work? Give an accounting situation where it might be most useful

> How is similarity matching different from clustering?

> How might classification be used in approving or denying a potential fraudulent credit card transaction?

> How might the data reduction approach be used in auditing?

> What is the difference between training data sets and test (or testing) data sets?

> The advantages of a relational database include limiting the amount of redundant data that are stored in a database. Why is this an important advantage? What can go wrong when redundant data are stored?

> What is the difference between a supervised and an unsupervised approach?

> Figures 3-1 through 3-4 suggest that volume and distance are the best predictors of “days to ship” for a wholesale company? Any other variables that would also be useful in predicting the number of “days to ship”?

> Compare and contrast the profiling data approach and the development of standard cost for a unit of production at a manufacturing company? Are they substantially the same or do they have differences?

> What is the purpose of a data dictionary? Identify four different attributes that could be stored in a data dictionary, and describe the purpose of each.

> Among the advantages of using a relational database is enforcing business rules. Based on your understanding of how the structure of a relational database helps prevent data redundancy and other advantages, how does the primary key/foreign key relationsh

> In the ETL process, one important step to process when transforming the data is to work with NULL, N/A, and zero values in the dataset. If you have a field of quantitative data (e.g., number of years each individual in the table has held a full-time job)

> The advantages of a relational database include integrating business processes. Why is it preferable to integrate business processes in one information system, rather than store different business process data in separate, isolated databases?

> Give an example of how Data Analytics creates value for accounting.

> Give an example of how Data Analytics creates value for businesses.

> What is the difference between a target and a class?

> Which attributes from the College Scorecard data would you need to compare cost of attendance across types of institutions (public, private non-profit, or private for-profit)??

> According to the text and your own experience, why is Tableau ideal for exploratory data analysis?

> To address the question “Will I receive a loan from LendingClub?” we had available data to assess the relationship among (1) the debt-to-income ratios and number of rejected loans, (2) the length of employment and number of rejected loans, and (3) the cr