Question 1

Raw data often must be scrubbed to remove extraneous data and other noise in order to become useful. This technique is known as:
A. Process, Scrub, and Import.
B. Extract, Transform, and Load.
C. Evaluate, Depopulate, and Finalize.
D. Filter, Coordinate, and Upload.

Accepted Answer

The technique of removing extraneous data and noise from raw data is known as Extract, Transform, and Load (ETL). ETL involves extracting the relevant data from a source, transforming it into a format that can be easily analyzed, and loading it into a target database or data warehouse. Therefore, option B is the correct choice. The other options are not related to the data cleansing process.

Question 2

Which of the following areas of financial reporting is most suitable for applying data analytics techniques?
A. Evaluation of estimates and valuations.
B. Variance reporting.
C. Calculating the components of equity.
D. Depreciation.

Accepted Answer

Evaluation of estimates and valuations involves significant judgments and assumptions. With data analytics techniques, auditors can analyze large volumes of data and identify unusual patterns or trends that may require further investigation. This can help auditors determine whether the estimates and valuations are reasonable and appropriate. Therefore, applying data analytics techniques to this area of financial reporting is most suitable.

Question 3

The Data Accountability and Trust Act of 2009 (DATA) is designed to standardize the format of files and fields typically used to support an external audit in given financial business processes.

Accepted Answer

The Data Accountability and Trust Act of 2009 (DATA) is actually focused on protecting consumers' personal information by requiring transparency and accountability from businesses that collect and use their data. It does not specifically address file and field formats for audits in financial processes.

Question 4

Which of the following best summarizes the two key limiting factors for business systems when dealing with Big Data?
A. Data storage capacity and processing power.
B. Data availability and software tools.
C. Database organization and transaction volume.
D. Analytic skills and software tools.

Accepted Answer

The two key limiting factors for business systems when dealing with Big Data are data storage capacity and processing power. As the size of data continues to increase, businesses need to have sufficient storage capacity to store the data and enough processing power to manage and analyze it effectively. Without these two elements in place, businesses may struggle to manage and make sense of the data they collect. The other options listed are also important factors to consider when dealing with Big Data, but they are not the primary limiting factors.

Question 5

The insight provided through data analytics can help companies in all of the following ways except:
A. Dictate the policies of external business partners.
B. Create more directed marketing campaigns.
C. Identify future opportunities and risks.
D. Affect internal business processes in order to improve productivity, utilization and growth.

Accepted Answer

While data analytics can provide valuable insights for companies to make informed decisions and improve various aspects of their business, it cannot dictate the policies of external business partners. Such decisions require negotiation and agreement between both parties.

Question 6

According to the results of the PWC's 18^th Annual Global CEO Survey, CEO's aren't yet ready to place a high value on data analytics.

Accepted Answer

According to the survey results, 85% of CEO's believe that data analytics are important to the future success of their business, indicating that they do place a high value on it.

Question 7

Which of the following is not one of the skill sets often associated with data analytics?
A. Mining and analyzing data.
B. Creating data structures and models.
C. Normalizing data structures.
D. Acquiring and cleansing data.

Accepted Answer

The answer of Which of the following is not one...

Question 8

Tableau can be differentiated from traditional analysis tools such as Excel because it is specifically designed to perform data analysis and visualization.

Accepted Answer

Tableau is specifically designed for data analysis and visualization, whereas Excel is a general-purpose spreadsheet program that can also perform data analysis. Tableau offers a wide range of visualization options and advanced analytics features that Excel does not have.

Question 9

Which of the following is the most likely application of data analytics for accountants to develop expertise in?
A. Directed marketing campaigns.
B. Scientific research.
C. Medical testing.
D. Domain knowledge of business functional areas.

Accepted Answer

The answer of Which of the following is the most...

Question 10

Data analytics can provide deep insight into financial data, but is not particularly useful when evaluating non-financial data such as social media.

Accepted Answer

Data analytics can be used to analyze non-financial data such as social media. In fact, social media data analytics is a growing field and can provide valuable insights into customer behavior, sentiment analysis, and marketing effectiveness.

Question 11

The process of scrubbing raw data to remove extraneous data and other noise in order to increase its usefulness is known as extract, transform and load.

Accepted Answer

The answer of The process of scrubbing raw data to...

Question 12

Data analytics is best described as the science of reducing extremely large datasets down to more manageable databases that can then be processed using traditional tools.

Accepted Answer

Data analytics involves using statistical and mathematical techniques to extract insights from data, not just reducing the size of datasets. While data reduction is sometimes a part of data analytics, it is not the central focus.

Question 13

Audit data standards (ADS) are standards for data files and fields typically needed to support an external audit in a given financial business process area.

Accepted Answer

Audit data standards (ADS) are indeed standards for data files and fields typically needed to support an external audit in a given financial business process area.

Question 14

As described in the text, which of the following best defines the term data analytics?
A. The ability to analyze data and draw conclusions.
B. The science of reducing extremely large datasets down to more manageable databases that can be processed using traditional tools.
C. The process of creating meaningful visualizations from extremely large datasets.
D. The science of examining raw data, removing excess noise, and organizing it in order to draw conclusions for decision making.

Accepted Answer

The answer of As described in the text, which of...

Question 15

Which of the following is the best definition of the term big data?
A. Databases measured in terms of zettabytes.
B. Datasets that are too large and complex for businesses' existing systems utilizing traditional capabilities.
C. Databases for businesses that generate more than one million electronic transactions per month.
D. Datasets generated by social media applications such as Facebook, Twitter, Tencent QQ, and Instagram.

Accepted Answer

Big data refers to datasets that are too large and complex for businesses' existing systems utilizing traditional capabilities. While the size of the dataset can vary, it is characterized by the complexity and the inability for traditional systems to handle it.

Question 16

Data analytics are likely to play a significant role in future audit activities.

Accepted Answer

As data becomes increasingly digital, auditors are turning to data analytics tools to analyze large volumes of data in less time and with greater accuracy. This allows auditors to identify patterns and anomalies that could indicate fraud or errors, and provides a more comprehensive picture of the clients' financial statements. Therefore, data analytics are expected to play a significant role in future audit activities.

Question 17

At its core, data analytics fits into the information value chain in which of the following ways?
A. The process of data analytics aims at transforming raw data into valuable information.
B. Data analytics aims to make an organization's conversion process more efficient.
C. Data analytics requires organizations to share synced data with upstream and downstream business partners.
D. The process of data analytics is geared toward providing additional insight into customer activities and preferences.

Accepted Answer

Data analytics is the process of examining data sets in order to draw conclusions about the information they contain, with the aim of transforming raw data into valuable insights and information that can help an organization make more informed decisions. While data analytics may certainly help a company make its conversion process more efficient, this is not its primary purpose, nor is it a requirement for working with analytical data. Similarly, while data syncing may be necessary to ensure that everyone within an organization is working with the same data sets, this has little to do with the process of data analytics at its core. Finally, while insights into customer activities and preferences are often an important part of data analytics, they are not the only goals of the process.

Question 18

Datasets that are too large and complex for businesses' existing systems utilizing traditional capabilities are refered to as big data.

Accepted Answer

Big data refers to datasets that are so large and/or complex that traditional data processing systems are unable to handle them effectively.

Question 19

How does data analytics play a vital role in today's business world?
A. By allowing data to be organized into predefined tables and fields.
B. By defining three main categories of classes that help organize a company's data structure models.
C. By examining data to generate models for predictions of patterns and trends.
D. By capturing the ever-increasing transaction activity of large companies.

Accepted Answer

Data analytics involves examining data to identify patterns, trends, and insights that can inform business decisions. This can help companies improve operational efficiency, identify new revenue streams, and better understand customer behavior. By using advanced analytics tools and techniques, companies can gain a competitive advantage and make more informed decisions about their business strategies.

Question 20

Which of the following best desribes the skill sets used in data analytics?
A. Building data warehouses; Populating data structures; Mining the data.
B. Acquiring/cleansing data; Creating data structures/models; Mining/analyzing data.
C. Developing data structures/models; Acquiring storage capacity; Analyzing the data.
D. Creating data; Building data structures; Piloting data studies.

Accepted Answer

The skill sets used in data analytics include acquiring/cleansing data, creating data structures/models, and mining/analyzing data. Building data warehouses and creating data are not specific tasks related to data analytics. Acquiring storage capacity and piloting data studies are also not necessary components of data analytics skill sets.

Quiz 9: Data Analytics in Accounting

Raw data often must be scrubbed to remove extraneous data and other noise in order to become useful. This technique is known as: A. Process, Scrub, and Import. B. Extract, Transform, and Load. C. Evaluate, Depopulate, and Finalize. D. Filter, Coordinate, and Upload.

Which of the following areas of financial reporting is most suitable for applying data analytics techniques? A. Evaluation of estimates and valuations. B. Variance reporting. C. Calculating the components of equity. D. Depreciation.

The Data Accountability and Trust Act of 2009 (DATA) is designed to standardize the format of files and fields typically used to support an external audit in given financial business processes.

Which of the following best summarizes the two key limiting factors for business systems when dealing with Big Data? A. Data storage capacity and processing power. B. Data availability and software tools. C. Database organization and transaction volume. D. Analytic skills and software tools.

According to the results of the PWC's 18th Annual Global CEO Survey, CEO's aren't yet ready to place a high value on data analytics.

Which of the following is not one of the skill sets often associated with data analytics? A. Mining and analyzing data. B. Creating data structures and models. C. Normalizing data structures. D. Acquiring and cleansing data.