Deck 1: Business Analytics With Management Science

Question 1

Structured, in-house operational databases are not included in the Big Data domain.

Answer 1

False

Question 2

The content of employee emails is an example of a non-structured data source.

Answer 2

True

Question 3

The increase in the amount of data available due to automatic data capture technologies is an example of Big Data velocity.

Answer 3

False

Question 4

The increase in the rate at which data flow into an organization due to online sales, mobile computing, smartphones, and online social networks is an example of Big Data velocity.

Question 5

The increase in the number of sources and data formats due to improved data capture technologies is an example of Big Data variety.

Question 6

Big Data demands that data scientists and managers implement new techniques and, above all, a new way of thinking.

Question 7

Business analytics is defined as a set of tools and techniques used to retrieve, process, transform, and analyze data in order to generate business insights and make better decisions.

Question 8

Databases and data warehouse technologies are an important part of business analytics.

Question 9

The main goal of prescriptive analytics is to summarize a sample, not use data to learn about the population that the sample of data is thought to represent.

Question 10

Histograms are a common tool used in predictive analytics.

Question 11

Predictive analytics uses statistical modeling to draw conclusions and predict behavior based on the assumption that what has happened in the past will continue to happen.

Question 12

The examples of Target, LinkedIn, First Tennessee, and many other companies that have implemented data analytics initiatives indicate that business analytics programs are more successful in large corporations.

Question 13

Spreadsheet modeling offers a high degree of data integrity and, as such, is an excellent tool for prescriptive analytics.

Question 14

Big Data models can sometimes lead to bad business results, conclusions, and recommendations due to inaccurate information.

Question 15

Mathematical models are often created through the process of abstraction and, as a result, can produce inaccurate results.

Question 16

Which of the following types of data is not included in the Big Data domain?

A) Structured, in-house operational databases
B) Structured, external databases
C) Non-structured data from social networks
D) Web server logs
E) All of the above data types are part of Big Data.

Question 17

Big Data includes both structured and non-structured data sources. Which of the following is usually considered to be a structured data source?

A) The content of emails
B) The content of web pages
C) The content of employee information
D) The content of daily memos
E) All of the above

Question 18

Big Data is usually characterized by three Vs: volume, velocity, and variety. Which of the following statements best describes the volume of data?

A) The amount of data available is significantly increased due to automatic data capture technologies.
B) The rate at which data flow into an organization has increased due to online sales, mobile computing, smartphones, and online social networks.
C) The number of sources and data formats has increased due to the increase of data capture technologies such as text and images from online social networks, images and voice from a camera, and voice recognition technologies, among others.
D) All of the above describe the volume of Big Data.

Question 19

Big Data is usually characterized by three Vs: volume, velocity, and variety. Which of the following statements best describes the velocity of data?

A) The amount of data available is significantly increased due to automatic data capture technologies.
B) The rate at which data flow into an organization has increased due to online sales, mobile computing, smartphones, and online social networks.
C) The number of sources and data formats has increased due to the increase of data capture technologies such as text and images from online social networks, images and voice from a camera, and voice recognition technologies, among others.
D) All of the above describe the velocity of Big Data.

Question 20

Big Data is usually characterized by three Vs: volume, velocity, and variety. Which of the following statements best describes the variety of data?

A) The amount of data available is significantly increased due to automatic data capture technologies.
B) The rate at which data flow into an organization has increased due to online sales, mobile computing, smartphones, and online social networks.
C) The number of sources and data formats has increased due to the increase of data capture technologies such as text and images from online social networks, images and voice from a camera, and voice recognition technologies, among others.
D) All of the above describe the volume of Big Data.

Question 21

Big Data demands that data scientists and managers implement new techniques and, above all, a new way of thinking. Specifically, Big Data requires that:

A) Managers think more anecdotally than probabilistically.
B) Managers learn to focus more on the signals than on the noise.
C) Managers apply business analytics more at the operational level than at the strategic level.
D) All of the above are required in the Big Data paradigm.

Question 22

What is business analytics?

A) A set of tools and techniques used to retrieve, process, transform, and analyze data in order to generate business insights
B) A set of tools and techniques used to retrieve, process, transform, and analyze data in order to make better decisions
C) The use of data for better decision making
D) All of the above are good definitions of business analytics.

Question 23

What is the difference between analytics and statistics?

A) Analytics includes statistics and other components such as databases, data warehouses, and optimization techniques.
B) Statistics includes analytics and other components such as databases, data warehouses, and optimization techniques.
C) Analytics and statistics are two completely different fields of study.
D) There is no difference; these concepts can be used interchangeably.

Question 24

Which of the following is a major field of study included in business analytics?

A) Descriptive analytics
B) Predictive analytics
C) Prescriptive analytics
D) All of the above

Question 25

Which of the following fields of business analytics can be used to effectively store and efficiently retrieve information?

A) Databases and data warehouses
B) Descriptive analytics
C) Predictive analytics
D) Prescriptive analytics

Question 26

Which of the following fields of business analytics can be used to report what has happened in the past?

A) Databases and data warehouses
B) Descriptive analytics
C) Predictive analytics
D) Prescriptive analytics

Question 27

Which of the following fields of business analytics uses past data to create models that predict the future?

A) Databases and data warehouses
B) Descriptive analytics
C) Predictive analytics
D) Prescriptive analytics

Question 28

Which of the following fields of business analytics uses optimization, heuristics, and/or simulation models to prescribe the best courses of action?

A) Databases and data warehouses
B) Descriptive analytics
C) Predictive analytics
D) Prescriptive analytics

Question 29

Which of the following fields of business analytics aims to summarize a sample instead of using data to learn about the population that the sample of data is thought to represent?

A) Databases and data warehouses
B) Descriptive analytics
C) Predictive analytics
D) Prescriptive analytics

Question 30

Which of the following is a tool commonly used in descriptive statistics?

A) Mean
B) Standard deviation
C) Variance
D) Stem and leaf diagrams
E) All of the above

Question 31

Which of the following is not a tool commonly used in descriptive statistics?

A) Histograms
B) Quartiles
C) Frequency distributions
D) Neural networks
E) All of the above

Question 32

Predictive analytics uses statistical modeling to draw conclusions and predict behavior based on the assumption that:

A) What has happened in the past will continue to happen in the future.
B) What has happened in the past will not happen in the future.
C) What has happened in the past has no impact on what will happen in the future.
D) None of the above are assumptions used in predictive analytics.

Question 33

Which of the following describes the change in the nature of management science to accommodate the need to process large volumes of data?

A) Reliance on spreadsheet modeling
B) Connection of optimization models with live operational databases
C) The use of distributed file systems technologies such as Hadoop to process a variety of data sources
D) All of the above are used by management scientists to process large volumes of data.

Question 34

Which of the following describes the change in the nature of management science to accommodate the need to process high-velocity data?

A) Reliance on spreadsheet modeling
B) Connection of optimization models with live operational databases
C) The use of distributed file systems technologies such as Hadoop to process a variety of data sources
D) All of the above

Question 35

Which of the following describes the change in the nature of management science to accommodate the need to process high variety of data?

A) Reliance on spreadsheet modeling
B) Connection of optimization models with live operational databases
C) The use of distributed file systems technologies such as Hadoop to process a variety of data sources
D) All of the above

Question 36

The examples of Target, LinkedIn, First Tennessee, and many other companies that have implemented data analytics initiatives indicate that:

A) Business analytics programs are more successful in large corporations.
B) Business analytics programs are more successful in medium-sized or small corporations.
C) Corporations must have a clear, step-by-step plan to implement any business analytics initiative.
D) All of the above are lessons learned by organizations that have successfully implemented business analytics.

Question 37

Which of the following statements does not reflect LinkedIn's approach to its "People You May Know" campaign?

A) LinkedIn uses information about its members that is housed in operational databases.
B) LinkedIn organizes information about its members in a data warehouse.
C) LinkedIn uses prescriptive analytics to generate reports and discover patterns.
D) LinkedIn uses predictive analytics to discover that speed is very important in receiving positive responses.
E) All of the above accurately describe LinkedIn's approach to its "People You May Know" campaign.

Question 38

Assume that you are a regular customer of a restaurant. Which of the following best describes the information management component of business analytics used by the restaurant to make you a more valuable customer?

A) Storing information about you and loading it into data warehouses
B) Investigating correlations, sampling customer data, and summarizing data
C) Determining the menu item that you will most likely order on your next visit
D) Offering coupons or discounts to maximize sales or profits

Question 39

Assume that you are a regular customer of a grocery store. Which of the following best describes the descriptive analytics component used by the store to make you a more valuable customer?

A) Storing information about you and loading it into data warehouses
B) Investigating correlations, sampling customer data, and summarizing data
C) Determining the grocery item that you will most likely purchase on your next visit
D) Offering coupons or discounts to maximize sales or profits

Question 40

Assume that you are a regular customer of a clothing store. Which of the following best describes the predictive analytics component used by the store to make you a more valuable customer?

A) Storing information about you and loading it into data warehouses
B) Investigating correlations, sampling customer data, and summarizing data
C) Determining the clothing item that you will most likely order on your next visit
D) Offering coupons or discounts to maximize sales or profits

Question 41

Assume that you are a regular customer of a clothing store. Which of the following best describes the prescriptive analytics component used by the store to make you a more valuable customer?

A) Storing information about you and loading it into data warehouses
B) Investigating correlations, sampling customer data, and summarizing data
C) Determining the clothing item that you will most likely order on your next visit
D) Offering coupons or discounts to maximize sales or profits

Question 42

Which of the following supports the assessment that descriptive and predictive analytics benefit from a high volume of data?

A) Statistical analysis and reliability of predictions are better when the population size increases.
B) A forecasting method with many input factors can predict better than the one with only a few input factors.
C) More data beats better modeling.
D) All of the above

Question 43

How do prescriptive models benefit from Big Data?

A) They are based on aggregated inputs, and their validity improves with high-volume data.
B) They often require iterative approaches to find optimal solutions.
C) Both a and b
D) None of the above

Question 44

Velocity is defined as the rate at which data flow into an organization. Which of the following can generate high data velocity?

A) Online sales
B) Mobile computing
C) Smartphones
D) Online social networks
E) All of the above

Question 45

Data variety is defined as a mix of different data sources in different formats. Which of the following does not generate high data variety?

A) An automated toll system that captures photos, license plates, and driver information
B) A sales transaction system that captures customer and product information
C) A weather station that captures satellite inputs, temperature sources, and live video streaming of weather events
D) All of the above generate data variety.

Question 46

Which of the following is considered to be a challenge that organizations face when analyzing Big Data?

A) Privacy invasion
B) Financial exposure
C) Mistaking noise for the signal
D) Poorly defined business problems
E) All of the above

Question 47

Which of the following is an advantage of using Excel modeling for prescriptive analytics?

A) Spreadsheets are easy to use and available at universities and other organizations.
B) Spreadsheet modeling offers a high degree of data integrity.
C) Spreadsheet models can be more accurate than specialized optimization software programs.
D) All of the above

Question 48

Which of the following explains why Big Data models can sometimes lead to poor business results, conclusions, and recommendations?

A) Big Data is sometimes associated with inaccurate information.
B) Mathematical models are often created through the process of abstraction.
C) Mathematical models often allow relevant information to enter the model.
D) All of the above