Chapter 10

Before data can be analyzed and be useful, it must be

scrubbed from extraneous data and noise.

Scan the environment—that is,

by scanning social media to identify potential risks and opportunities to the firm.

Audit data standards were developed by the following party to facilitate audits.

American Institute of Certified Public Accountants

Variety

The form of the data Unstructured and unprocessed data, such as comments in social media, emails, global positioning system (GPS) measurements, etc

Data Reliability

Is the data clean?

Storage

Many companies choose to use a cloud platform to lower the cost of data storage

In financial accounting, data analytics may be used to

Scan the environment

Addresses questions of Prescriptive Analytics

What is the level of sales needed to breakeven? How can revenues to maximized if there is a trade war with China? Should the company lease or buy its headquarters office? Should the company make its own products or outsource production to another company?

Diagnostic Analysis

Why Did it Happen? Analysis performed to investigate the underlying cause of a phenomenon

Addresses questions of Diagnostic Analysis

Why did advertising expense increase, but sales fall? Why did we experience an unfavorable labor rate variance last year? Why did overall tax increase even though net income did not?

Diagnostic analysis addresses which of the following questions? Why did it happen? What should we do based on what we expect will happen? What happened? Will it happen in the future?

Why did it happen?

Predictive Analysis

Will it Happen in the Future? Analysis performed to provide foresight by identifying patterns in historical data

Data Accessibility

can we get the needed data to answer the question posed?

Big Data

data sets too large and complex for businesses' existing systems to handle utilizing their traditional capabilities to capture, store, manage and analyze these datasets

Counts, totals and sums are specific types of ______ analysis employed. diagnostic prescriptive descriptive predictive

descriptive

Audit Data Standards provide the following benefits:

Reduces the time and effort Works well with standard audit and risk analytic Allows software vendors (such as ACL Inc.) to produce data Facilitates testing of the full population of transactions Connects/interacts well with XBRL GL Standards

True or false: Data analytics is defined as the science of examining raw data (now often Big Data), removing excess noise from the dataset, and organizing the data with the purpose of drawing conclusions for decision making.

True

Descriptive Analysis

What Happened? Analysis performed that characterizes, summarizes and organizes past performance.

Descriptive analysis addresses which of the following questions? Multiple choice question. What should we do based on what we expect will happen? Why did it happen? What happened? Will it happen in the future?

What happened?

The data analytics skill sets that should be developed are all but the following: Acquiring/cleansing data Decision making Mining/Analyzing data Creating data structure

Decision making

According to the textbook, audit data standards include all but the following benefits to accountants and auditors. Lends itself to analysis by managerial accountants seeking to lower costs Facilitates testing of the full population of transactions Reduces the time and effort involved in accessing data Interacts well with XBRL GL standards

Lends itself to analysis by managerial accountants seeking to lower costs

By using data analytics, auditors are able to spend

Less time looking for evidence Allow more time for presenting their findings and making judgments.

True or false: Auditors may monitor blogs and social media to assess the probability of a goodwill write-down

True

True or false: Auditors may monitor blogs and social media to assess the probability of a goodwill write-down.

True

The first step in the AMPS model is to _____. ask management what questions they have ask the question assess the data address the question

ask the question

The AMPS Model

1.Ask the Question 2.Master the data 3.Perform the analysis 4.Share the story

A study from McKinsey Global Institute estimates that Big Data could generate up to _____$ trillion in value per year in just a subset of industries impacted

3

Data questions include:

Data Accessibility Data Reliability Data Integrity Data Type

Semi-Structured Data

Data that has elements of both structured (high organized) and unstructured (not highly organized data) data

Unstructured Data

Data without internal organization (or structure) EX:Blogs, social media and pictures posted in IG

Addresses questions of Descriptive Analysis

Did we make a profit last year? How much did we pay in federal taxes last year? How long have the existing accounts receivable been past due?

ETL stands for which process for scrubbing raw data to make it ready for analysis? Multiple choice question. Extract, Translate, and Load Extrapolate, Transform, and Load Evaluate, Translate, and Load Extract, Transform, and Load

Extract, Transform, and Load

True or false: In general, data analytics requires the auditor to pull data at the client site before an external audit is completed.

False

True or false: Audit data standards are a set of data standards in preparation for the internal audit.

False Audit data standards are a set of data standards for the external audit.

True or false: Data analytics allows auditors to vastly expand sampling beyond current traditional sample sizes, but does not allow the ability to test the full population of transactions.

False Data analytics allows auditors to vastly expand sampling beyond current traditional sample sizes and the ability to test the full population of transactions.

According to the textbook, audits are expected to provide all but the following above and beyond the assurance perspective. Help companies improve efficiency Help companies anticipate future problems Help companies refine processes Help companies reduce future audit fees

Help companies reduce future audit fees

Structured Data

Highly organized data that fits nicely in a table or a database. EX: Balance sheet or income statement

Data Integrity

Is accurate, valid and consistent over time?

Data Type

Is the data structured? is the data internal? are there privacy concerns with the data?

According to the textbook, audit data standards include all but the following benefits to accountants and auditors. Facilitates testing of the full population of transactions Interacts well with XBRL GL standards Is useful for those preparing tax returns Allows software vendors to produce data extraction for those that follow audit data standards (ADS)

Is useful for those preparing tax returns

The data analytics skill sets that should be developed are all but the following: Multiple choice question. Creating data structures/models Mining/Analyzing data Acquiring/cleansing data Knowledge of audit data standards

Knowledge of audit data standards

Volume

The massive amount of data involved The sheer amount of data, regardless of its source Might come from corporate systems, clickstream data from social media, from the government, from the Internet search engines, or just the Internet in general.

Extract, Transform, and Load (ETL)

The process of cleaning and scrubbing the data before data analysis can take place

Processing Power

The processing power required to obtain information valuable to the company could be enormous or even impossible.

Veracity

The quality of the data Including extent of cleanliness (without errors or data integrity issues), reliability and representationally faithful

Data Analytics

The science of examining raw data (now often Big Data) Removing excess noise from the dataset Organizing the data with the purpose of drawing conclusions about that information

Velocity

The speed that the data is being generated or the rate that data is being analyzed The fact that the data comes in at quick speeds or in real time, such as streaming videos and news feeds

The analysis needed to address the question, 'Did return on assets improve or decline last year?', is _____ analysis. The analysis needed to address the question, 'Did we make a profit last year?', is _____ analysis. prescriptive predictive diagnostic descriptive

descriptive

Addressing the question, 'Why did sales, general and administrative expense increase relative to the industry', is an example of _____ analysis. Addressing the question, 'Why did advertising expense increase, but sales increase', is an example of _____ analysis. prescriptive diagnostic predictive descriptive

diagnostic

Looking for anomalies and outliers are specific types of ______ analysis employed. diagnostic predictive prescriptive descriptive

diagnostic

Data analytics plays a very critical role in the

future of audit.

The more _____ the question is, the better chance it has of being answered. narrow interesting broad

narrow

Classification and regression are specific types of ______ analysis employed. prescriptive predictive diagnostic descriptive

predictive

Forecasting whether a company will go bankrupt is an example of ______ analysis. The analysis needed to address the question, 'Can we forecast whether the company will have a profit next year?', is _____ analysis. The analysis needed to address the question, 'Will these financial statements need to be restated?', is _____ analysis. descriptive predictive diagnostic prescriptive

predictive

Addressing the question, "What should we do, based on what we expect will happen" is an example of ______ analysis. The analysis needed to address the question, 'How can revenues be maximized if our employees go on strike?', is _____ analysis. The analysis needed to address the question, 'What level of sales is needed to breakeven?', is _____ analysis. diagnostic descriptive prescriptive predictive

prescriptive

Optimization and what-if scenarios are specific types of ______ analysis employed. prescriptive diagnostic descriptive predictive

prescriptive

The "S" in the AMPS model stands for _____ . Multiple choice question.

share the story

Data Analytics professionals estimate that they spent between _________% and ________% of their time to cleaning data so it can be analyzed.

50 ; 90`

Data analytics professionals spend up to ___________ % of their time cleaning data for analysis?

90

Audit Data Standards (ADS)

A set of standards for data files and fields typically needed to support an external audit in a given financial business process area.

Which party would have the most interest in monitoring blogs and social media to assess the probability of the collectibility of bad debts? Stock exchange Customers Suppliers Company accountant

Company accountant

True or false: Audits do not provide value beyond the financial perspective and providing assurance.

False Reason: Audits not only yield important findings from a financial perspective, but also information that can help companies refine processes, improve efficiency and anticipate future problems

True or false: Data analytics comes up with computer algorithms that make decisions automatically without human intervention.

False Reason: Data analytics are suggestive. They examine raw data, remove excess noise, and organize the data with the purpose of assisting with decision making.

Data analytics often involves

The technologies, systems, practices, methodologies, databases, and applications used to analyze diverse business data to help organizations make sound and timely business decisions

True or false: Data analytics is useful for a business to examine patterns and trends in large datasets.

True

True or false: The phrase "Your data won't speak unless you ask it the right data analysis questions" really speaks to the expertise the accountant can offer by asking questions that are answerable by data

True The accountant has expertise knowing what data is available to answer the question.

Big Data is often described by the four Vs

Volume Variety Velocity Veracity

Prescriptive Analytics

What Should We Do, Based on What We Expect Will Happen? Analysis performed which identifies the best possible options given constraints or changing conditions

Addresses questions of Predictive Analysis

What is the chance the company will go bankrupt? What is our expected sales and income next year? Can we predict if the financial statements will be misstated? Will the borrower pay us back the loan we've granted her?

Companies generally face two important limiting factors in their business systems when dealing with Big Data:

storage and processing

The cost to scrub the data includes

the salaries of the data analytics scientists and the cost of the technology to prepare and analyze the data