Question 1

IBM's Slamtracker,which analyzes years of Grand Slam tennis data to compare historic head-to-head statistics of competitors to predict keys to winning a match,is an example of which kind of analysis?
A)Descriptive
B)Competitive
C)Prescriptive
D)Historical
E)Predictive

Accepted Answer

Slamtracker uses historic data to predict the outcome of future matches, making it a predictive analysis tool.

Question 2

The analysis that discovers interesting relationships between items purchased on a single ticket (e.g.in the same shopping cart)of consumers is
A)data harmonization.
B)data mining.
C)data fusion.
D)neural networks.
E)visualization.

Accepted Answer

The analysis of discovering interesting relationships between items purchased on a single ticket is a form of data mining. Data mining involves extracting useful information from large data sets, including identifying patterns and relationships between variables. In this case, the data set is the items purchased on a single ticket, and the analysis is focused on finding relationships between those items that can inform marketing or sales strategies.

Question 3

Creating charts,graphs,images,diagrams.and even word clouds that allow for better communication of data is an example of
A)data fusion.
B)visualization.
C)neural networks.
D)harmonization
E)data mining.

Accepted Answer

Visualization refers to the use of images, charts, graphs, and diagrams to communicate data effectively. This method helps in identifying patterns, trends, and outliers in the data that might be difficult to spot in tabular form. The use of word clouds may also help to identify frequently occurring terms in a dataset. Data fusion refers to combining data from multiple sources to provide a unified view of the information, while neural networks and data mining refer to specific techniques for data analysis. Harmonization refers to the process of ensuring that data from different sources can be compared and combined. However, none of these options describes the practice of creating visual aids to improve data communication as well as option B.

Question 4

The analysis that focuses on future-oriented,potential behaviors as opposed to classifying past behaviors is known as
A)future analysis.
B)predictive analysis.
C)descriptive analysis.
D)presumptive analysis.
E)speculative analysis.

Accepted Answer

The description matches with the definition of predictive analysis, which is analyzing future-oriented potential behaviors rather than past behaviors. Option A, C, D, and E do not accurately describe this type of analysis.

Question 5

A key term in prescriptive analysis is
A)randomization.
B)differentiation.
C)optimization.
D)experimentation.
E)amortization.

Accepted Answer

Prescriptive analysis focuses on identifying the best course of action to take in a given situation. This involves optimization, or finding the decision that will maximize the desired outcome. Randomization refers to a technique used in experimental design, differentiation generally refers to mathematical operations, experimentation involves actual testing of different scenarios or interventions, and amortization refers to paying off a debt over a period of time. Therefore, the best choice is optimization (C).

Question 6

What statement best describes what prescriptive analysis is used for?
A)To uncover explanatory and predictive models of business performance based on the relationship between data inputs and business outcomes.
B)To understand business performance.
C)To extract patterns from large datasets.
D)To determine a set of high-value alternative actions for the purposes of improving business performance.
E)To determine if a customer can be cross-sold or up-sold a product at the point of purchase.

Accepted Answer

Prescriptive analysis is used to determine a set of high-value alternative actions for the purposes of improving business performance. It goes beyond predictive analysis, which only provides insights into what may happen in the future, and provides specific recommendations on what actions to take to achieve the desired outcome.

Question 7

Taking multiple,random samples from an existing data set and running thousands of "what if" analyses,each with different assumptions about market conditions and other marketplace dynamics,is an example of which of the following?
A)Regression analysis
B)Trend analysis
C)Time series analysis
D)Simulation analysis
E)Spectral analysis

Accepted Answer

The given scenario describes the process of simulation analysis, where random samples are taken from an existing data set and different assumptions are made for multiple "what if" analyses. Simulation analysis is a technique used to model real-world business scenarios in a controlled environment to observe their outcomes.

Question 8

Combining real-time sales data with real-time social media mentions in order to better understand consumer sentiment toward an advertising campaign is an example of which data analysis technique?
A)Neural networks
B)Affinity
C)Data mining
D)Data fusion
E)Harmonization

Accepted Answer

Data fusion is the process of integrating multiple sets of data from different sources to obtain a more complete and accurate understanding of a situation or phenomenon. In this case, real-time sales data and real-time social media mentions are being combined to gain insights into consumer sentiment towards an advertising campaign.

Question 9

The analysis that Major League Baseball uses to create its schedule each year,to optimize stadium commitments,travel,hotel,sponsorships,and other factors is an example of
A)descriptive analysis.
B)prescriptive analysis.
C)chronological analysis.
D)predictive analysis.
E)spatial analysis.

Accepted Answer

The analysis used by Major League Baseball to create its schedule is aimed at providing recommendations or solutions that optimize various factors such as stadium commitments, travel, hotel, sponsorships, and other factors. This makes it an example of prescriptive analytics, which is used to prescribe the best solutions or actions to achieve specific goals or objectives. Therefore, option B) is the best choice for this scenario.

Question 10

Which of the following statements best represents the analytics skills problem of Big Data integration?
A)Big Data analytics is a discipline too new to provide meaningful employment opportunities.
B)Most companies have not yet accumulated enough data to have a need for Big Data analytics.
C)There is too much data and companies lack the right skills to manage data effectively.
D)The level of skill required for Big Data analytics is too low to attract quality job candidates into the profession.
E)There is no analytics skills problem associated with Big Data.

Accepted Answer

The statement "There is too much data and companies lack the right skills to manage data effectively" best represents the analytics skills problem of Big Data integration. With the increase in data volume, variety and velocity, there is a growing need for professionals who are skilled in analyzing Big Data. However, most companies lack the right skills to manage data effectively, and this has become a major roadblock to effective Big Data integration.

Question 11

_________ analysis tries to uncover explanatory and predictive models of business performance based on the relationship between data inputs and business outcomes.
A)Regression
B)Descriptive
C)Predictive
D)Perceptive
E)None of these are correct.

Accepted Answer

Predictive analysis is specifically designed to uncover explanatory and predictive models of business performance by analyzing the relationship between data inputs and business outcomes. Regression analysis can sometimes be included in predictive analysis but is not designed explicitly for it. Descriptive analysis simply summarizes the data without attempting to make any predictions. Perceptive analysis is not a commonly used term in data analysis.

Question 12

Discovering data-based trends by analyzing sequences of data over successive times to not only recognize the data pattern but forecast how the data will extend into the future is the goal of
A)regression analysis.
B)trend analysis.
C)time series analysis.
D)simulation analysis.
E)spectral analysis.

Accepted Answer

Time series analysis involves analyzing data over successive times to identify patterns and forecast future trends. Regression analysis involves identifying the relationship between variables, but not necessarily over time. Trend analysis involves identifying general patterns over time, but may not involve forecasting future trends. Simulation analysis involves creating a model to imitate a real-world scenario and observe the results. Spectral analysis involves decomposing a signal into its component frequencies.

Question 13

The analysis technique to consider when searching for nonlinear patterns in data is
A)visualization.
B)data fusion.
C)data modeling.
D)data mining.
E)neural networks.

Accepted Answer

Nonlinear patterns in data may not be easily recognizable through traditional analytical techniques. Therefore, a nonlinear modeling technique such as neural networks may be the most effective approach to identify and analyze these patterns.

Question 14

Which of the following is NOT considered a descriptive analysis technique?
A)Data harmonization
B)Data mining
C)Data fusion
D)Neural networks
E)Visualization

Accepted Answer

The answer of Which of the following is NOT considered...

Question 15

Which of the following best describes what prescriptive analysis is?
A)To recommend the best course of action among the firm's various options.
B)To predict a future outcome with some degree of confidence.
C)To understand the current context.
D)None of these are correct.
E)All of these are correct descriptions of descriptive analysis.

Accepted Answer

Prescriptive analysis involves recommending the best course of action among different options.

Question 16

A key challenge of Big Data is integration.Which of the following is NOT one of the areas in which companies are challenged with Big Data integration?
A)Integration of a firm's internal transaction data
B)Access to data
C)Analytic skills
D)Retrieval of data
E)Integration of data within and between firms

Accepted Answer

The answer of A key challenge of Big Data is...

Question 17

Recognizing patterns,such as identifying fraudulent insurance claims made by otherwise consistent policyholders,is an example of which kind of descriptive analysis technique?
A)Data screening
B)Visualization
C)Neural networks
D)Data fusion
E)Data mining

Accepted Answer

The answer of Recognizing patterns,such as identifying fraudulent insurance claims...

Question 18

The descriptive analysis technique whose goal is to integrate and analyze data from various sources as opposed to relying on only a single source is known as
A)data harmonization.
B)data mining.
C)data fusion.
D)neural networks.
E)visualization.

Accepted Answer

Data fusion is a technique where data from different sources are combined and analyzed to provide a more complete understanding of a particular phenomena or situation. It involves integrating and merging data sets to reduce redundancy, remove inconsistencies and generate more accurate and reliable insights. Data harmonization, on the other hand, involves standardizing data from different sources to make them compatible and comparable. While data mining involves the use of statistical and computational algorithms to extract useful information from large data sets, neural networks use a complex system of interconnected artificial neurons to analyze data, and visualization tools create visual representations of data to facilitate understanding.

Question 19

The analysis technique that involves seeing how a dependent variable might change when one or more independent variables changes,such as to see if a customer can be cross-sold or up-sold at the point of purchase is known as
A)purchase analysis.
B)regression analysis.
C)descriptive analysis.
D)time series analysis.
E)simulation analysis.

Accepted Answer

Regression analysis involves examining the relationship between one or more independent variables and a dependent variable to see how changes in the independent variables affect the dependent variable. This technique can be used to analyze customer behavior and predict if they are likely to make additional purchases (cross-sell or up-sell) at the point of purchase.

Question 20

A wealth of barcode transaction data is collected by merchants when customers make purchases. Which one of the following scenarios does NOT represent one of the typical Big Data integration challenges in using these transactional data?
A)Getting merchandising ideas by doing a market basket analysis
B)Linking the transaction data to a decision support system for ease of in-store price changes
C)Creating personalized promotions using the store's loyalty program
D)Combining barcode transaction data with customer Facebook status updates about service quality
E)All of these represent typical Big Data integration challenges

Accepted Answer

The answer of A wealth of barcode transaction data is...

Quiz 6: Decision Support Systems: Working With Big Data

IBM's Slamtracker,which analyzes years of Grand Slam tennis data to compare historic head-to-head statistics of competitors to predict keys to winning a match,is an example of which kind of analysis?

The analysis that discovers interesting relationships between items purchased on a single ticket (e.g.in the same shopping cart) of consumers is

Creating charts,graphs,images,diagrams.and even word clouds that allow for better communication of data is an example of

The analysis that focuses on future-oriented,potential behaviors as opposed to classifying past behaviors is known as

A key term in prescriptive analysis is

What statement best describes what prescriptive analysis is used for?

Taking multiple,random samples from an existing data set and running thousands of "what if" analyses,each with different assumptions about market conditions and other marketplace dynamics,is an example of which of the following?

Combining real-time sales data with real-time social media mentions in order to better understand consumer sentiment toward an advertising campaign is an example of which data analysis technique?

The analysis that Major League Baseball uses to create its schedule each year,to optimize stadium commitments,travel,hotel,sponsorships,and other factors is an example of

Which of the following statements best represents the analytics skills problem of Big Data integration?

_________ analysis tries to uncover explanatory and predictive models of business performance based on the relationship between data inputs and business outcomes.

Discovering data-based trends by analyzing sequences of data over successive times to not only recognize the data pattern but forecast how the data will extend into the future is the goal of

The analysis technique to consider when searching for nonlinear patterns in data is

Which of the following is NOT considered a descriptive analysis technique?

Which of the following best describes what prescriptive analysis is?

A key challenge of Big Data is integration.Which of the following is NOT one of the areas in which companies are challenged with Big Data integration?

Recognizing patterns,such as identifying fraudulent insurance claims made by otherwise consistent policyholders,is an example of which kind of descriptive analysis technique?

The descriptive analysis technique whose goal is to integrate and analyze data from various sources as opposed to relying on only a single source is known as

The analysis technique that involves seeing how a dependent variable might change when one or more independent variables changes,such as to see if a customer can be cross-sold or up-sold at the point of purchase is known as

A wealth of barcode transaction data is collected by merchants when customers make purchases. Which one of the following scenarios does NOT represent one of the typical Big Data integration challenges in using these transactional data?