Question 1

Data mining offers organizations a decision-enhancing environment to exploit opportunities by transforming data into a strategic weapon.

Accepted Answer

Data mining allows organizations to analyze large amounts of data to identify patterns, trends, and insights that can be used to make informed decisions and gain a competitive advantage. By transforming data into useful information, organizations can make better strategic decisions and achieve their goals more effectively.

Question 2

Two types of categorical data are nominal data and ordinal data.

Accepted Answer

Nominal data is data that is divided into categories that do not have an inherent order or sequence, while ordinal data is data that is divided into categories that do have an inherent order or sequence.

Question 3

Mass,length,time,plane angle,energy,and electric charge are examples of physical measures whose data are represented in interval scales.

Accepted Answer

Mass, length, time, plane angle, energy, and electric charge are examples of physical measures whose data are represented in ratio scales, not interval scales, because they have a meaningful zero point that allows for the comparison of absolute magnitudes.

Question 4

Technically speaking,data mining is a process that uses statistical,mathematical,and artificial intelligence techniques to extract and identify useful information and subsequent knowledge from large sets of data.

Accepted Answer

This statement accurately describes the concept of data mining.

Question 5

Associations are a type of pattern that discovers time-ordered events,such as predicting that an existing banking customer who already has a checking account will open a savings account followed by an investment account within a year.

Accepted Answer

Associations in data mining are used to find patterns that describe items that often occur together, but they do not inherently involve time-ordered events. Sequence or time-series analysis would be more appropriate for predicting time-ordered events.

Question 6

The variable marital status can be categorized using the codes (1)single, (2)married,and (3)divorced.These codes are examples of ordinal data.

Accepted Answer

Ordinal data represents values that can be sorted or ranked in a specific order. In this case, the codes for marital status can be arranged in a specific order - single (1), married (2), and divorced (3).

Question 7

Data mining is a prime candidate for better management of companies that are data-rich,but knowledge-poor.

Accepted Answer

Data mining is a valuable tool for companies that have large amounts of data but are lacking in knowledge or insights. It enables them to extract patterns and trends from the data, which can then be used to make informed decisions and improve overall efficiency and effectiveness.

Question 8

Data types such as date/time,unstructured text,image,and audio need to be converted into some form of categorical or numeric representation before they can be processed by data mining algorithms.

Accepted Answer

Data mining algorithms typically require categorical or numerical data to operate on, thus data types such as date/time, unstructured text, image, and audio need to be converted into a suitable representation prior to analysis.

Question 9

Data mining is a way for companies to develop business intelligence from their data to gain a better understanding of their customers and operations and to solve complex organizational problems.

Accepted Answer

Data mining does help in developing business intelligence from data that can aid companies in improving their understanding of customers, optimizing operations, and addressing complex issues. Therefore, option A is correct.

Question 10

The first step in the data mining process is to understand the relevant data from the available databases.

Accepted Answer

The first step in the data mining process is to understand the business problem or objective, which guides the subsequent steps including understanding the relevant data.

Question 11

Compared to the other steps in CRISP-DM,data preprocessing consumes the most time and effort; most believe that this step accounts for roughly 80 percent of the total time spent on a data mining project

Accepted Answer

Data preprocessing involves cleaning, transforming, and preparing the data for analysis, which is a time-consuming process. Most data scientists spend a considerable amount of time on this step, often up to 80 percent of the total project time.

Question 12

The data mining environment is usually a client-server architecture or a Web-based information systems architecture.

Accepted Answer

The data mining environment can be implemented as a client-server architecture or a Web-based information systems architecture. In a client-server architecture, the data mining tools and algorithms are installed on a central server, and the clients access the server through a network. In a Web-based information systems architecture, the data mining tools and algorithms are made available through a Web interface, and the users can access them through a Web browser. Both architectures have their advantages and disadvantages, and the choice depends on the specific requirements of the application.

Question 13

Clustering partitions a collection of things,such as objects and events presented in a structured dataset into segments whose members share similar characteristics.

Accepted Answer

Clustering is the process of dividing a dataset into groups or clusters based on the similarities among the observations in the dataset. Each cluster contains objects that are similar to each other and dissimilar to objects in other clusters. The aim of clustering is to find the underlying structure or patterns in the data.

Question 14

Data mining requires a separate,dedicated database.

Accepted Answer

Data mining can be done on any database that contains the relevant data. It does not require a separate or dedicated database.

Question 15

In order to be applied successfully,a data mining study must be viewed as a set of automated software tools and techniques.

Accepted Answer

Data mining success relies not only on the use of automated tools and techniques but also on the understanding of the domain, data interpretation, and integration with decision-making processes.

Question 16

Business analytics cannot be conducted in real time because it includes components such as metrics and reengineering tools.

Accepted Answer

Business analytics can be conducted in real time using tools and technologies that allow for data processing, analysis and visualization in real time. Metrics and reengineering tools can also be integrated into these tools to provide a more comprehensive analysis.

Question 17

A common example of interval scale measurement is temperature on the Celsius scale.

Accepted Answer

Temperature on the Celsius scale is an example of interval scale measurement. It has equal intervals between each scale point, but there is no true zero point (i.e., the absence of temperature is not the same as a value of zero).

Question 18

At the highest level of abstraction,all data can be divided into interval data and ratio data.

Accepted Answer

At the highest level of abstraction, all data can be divided into two main categories: qualitative (or categorical) data and quantitative (or numerical) data. Interval data and ratio data are subcategories of quantitative data.

Question 19

Cross-Industry Standard Process for Data Mining,or CRISP-DM,is one of the most popular
nonproprietary standard methodologies for data mining.

Accepted Answer

CRISP-DM is indeed one of the most popular nonproprietary standard methodologies for data mining.

Question 20

Predictions tells the nature of future occurrences of certain events based on what has happened in the past,such as predicting the winner of the Super Bowl or forecasting the absolute temperature of a particular day.

Accepted Answer

Predictions are based on past events and data to forecast future occurrences.

Quiz 5: Data Mining for Business Intelligence