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Management Information Systems > Exam 2- Chapters 5 and 12 > Flashcards

Exam 2- Chapters 5 and 12 Flashcards

1
Q

T or F: The process of acquiring, keeping, and managing data is becoming increasingly difficult.

A

True

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1
Q

All information technology applications require:

A

data

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2
Q

Data should be of high quality, meaning it should be what 7 things?

A
  1. Accurate
  2. Complete
  3. Timely
  4. Consistent
  5. Accessible
  6. Relevant
  7. Concise
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3
Q

What are the 8 difficulties of managing data?

A
  1. The amount of data is increasing with time.
  2. Data is frequently stored in numerous servers and locations
  3. Data are generated from multiple resources
  4. New data is constantly being developed, and this data must be managed; data also becomes less current over time
  5. Data are subject to data rot
  6. Data security, quality, and integrity are easily jeopardized.
  7. Federal regulations complicate data management and companies are drowning in data
  8. Big Data
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4
Q

Inconsistent data prevents a company from what?

A

Developing a unified view of core business information

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5
Q

a collection of data held by one group that is not easily accessible by other groups

A

data silo

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6
Q

One major method to remove data silos is through ________ ________ _________.

A

cloud data management

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7
Q

What are three issues with data silo’s?

A
  1. Hinder the process of gaining actionable insights from organizational data
  2. Create barriers to an overall view of the enterprise and its data
  3. Delay digital transformation efforts
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8
Q

Data that are continuously generated by point-of-sale systems, clickstream data, social media, and sensors

A

Data streams

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9
Q

Point of Sale systems collect data in _____ _____.

A

real time

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10
Q

the information that is collected during the customer sales transaction (like name, product identification number, unit price of each item, etc.)

A

point-of-sale data

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11
Q

What are the four types of data streams?

A
  1. Point-of-Sale Data
  2. Clickstream Data
  3. Social Media Data
  4. Sensor Data
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12
Q

the data that visitors and customers produce when they visit a website and click on hyperlinks

A

clickstream data

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13
Q

What type of data stream would this be: data that includes shares, likes and dislikes, ratings, reviews, recommendations, and comments.

A

social media data

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14
Q

a system in which any object, natural or manmade, contains internal or external wireless sensor(s) that communicate with each other without human interaction. What type of data stream does this relate to?

A

The Internet of Things (IoT); sensor data

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15
Q

monitors and reports data on physical and environmental conditions around it, such as temperature, sound, pressure, vibration, and movement

A

sensor data

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16
Q

What can sensors do?

A

Control physical systems, such as opening and closing a valve and adjusting the fuel mixture in your car

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17
Q

T or F: Being able to collect massive amounts of data from many different sources is a double-edged sword.

A

True

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18
Q

problems with the media on which the data are stored

A

data rot

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19
Q

What are the two aspects of data rot?

A
  1. Over time, temp, humidity, and exposure to light can cause physical problems with storage media and make it difficult to access data
  2. Finding the machines needed to access the data can be difficult
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20
Q

What three things are critical for data, yet easily jeopardized?

A

Security, quality, and integrity

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21
Q

Today capturing data is (hard/easy) and storing that data is relatively (expensive/inexpensive).

A

easy; inexpensive

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22
Q

An increasing number of companies are turning to ________ to help them make sense of their data.

A

Enigma

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23
Q

a data management and business intelligence company that specializes in data integration and analytics.

A

Enigma

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24
Q

Enigma notes that it has always been difficult for banks to share data, principally due to ________ ______.

A

privacy concerns

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25
Q

a set of programs that provide users with tools to create and manage a database

A

database management system (DMS)

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26
Q

the process of accepting liability under an insurance policy, thus guaranteeing payment in case loss or damage occurs

A

underwriting

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27
Q

T or F: Databases and database management systems are essential to all areas of business, so they must be carefully managed.

A

True

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28
Q

Why do we focus on the RELATIONAL database model?

A

Because it is popular and easy to use

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29
Q

Database models, like the hierarchical and network models, are the responsibility of the _____ _____ and are NOT used by ___________ ________.

A

MIS function; organizational employees

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30
Q

What are two examples of relational databases?

A
  1. Microsoft Access
  2. Oracle
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31
Q

The relational database model is based on the concept of _____-________ tables.

A

two-dimensional

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32
Q

A relational database is usually designed with which of the following:
1. a big table that contains all of the records and attributes
2. a number of related tables

A
  1. a number of related tables
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33
Q

Relational database rows contain ____ and columns contain _____.

A

records; attributes

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34
Q

A key to designing an effective database is the _____ ______.

A

data model

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35
Q

a diagram that represents entities in the database and their relationships

A

data model

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36
Q

a person, place, a thing, or an event– such as a customer, an employee, or a product– about which an organization maintains information.

A

entity

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37
Q

Entities can typically be identified in the user’s _____ _____. A ______ generally describes an entity.

A

work environment; record

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38
Q

each row in a relational table, which is a specific, unique representation of the entity

A

instance of an entity

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39
Q

A student in a universities student database would be an ______. A particular student would be an ______ of the student entity.

A

entity; instance

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40
Q

each characteristic or quality of a particular entity

A

attribute

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41
Q

T or F: an example of an entity attribute of a customer would be customer name

A

True

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42
Q

T or F: entity attribute of a product could be product color

A

True

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43
Q

one field that uniquely identifies a record so that it can be retrieved, updated and sorted

A

primary key

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44
Q

What’s an example of a primary key?

A

a unique student id number

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45
Q

another field that has some identifying information but typically does not identify the record with complete accuracy

A

secondary key

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46
Q

What’s an example of a secondary key?

A

a students major

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47
Q

a field (or group of fields) in one table that uniquely identifies a row of another table; used to establish and enforce a link between two tables

A

foreign key

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48
Q

highly organized data in fixed fields in a data repository such as a relational database

A

structured data

49
Q

data that do not reside in a traditional relational database

A

unstructured data

50
Q

What are three examples of unstructured data?

A
  1. E-mail messages
  2. Videos/images
  3. Powerpoint presentations
51
Q

80-90% of data in an organization are (structured/unstructured)

A

unstructured

52
Q

T or F: Databases typically process data in real time

A

True

53
Q

Do users have access to databases?
If not, where can users access data for decision making?

A

NO; data warehouses

54
Q

The world generates over ___ ______ of data each year.

A

one zetabyte

55
Q

The amount of data produced worldwide is increasing by ___% each year.

A

50%

56
Q

Most stored information in the world today (98%) is (digital/non-digital)

A

digital

57
Q

a collection of data that is so large and complex that it is difficult to manage using traditional database management systems

A

Big Data

58
Q

large amounts of traditional data

A

big data

59
Q

Why does Big Data systems perform well?

A

Bc they contain huge amounts of data on which to base their predictions

60
Q

diverse, high-volume, high-velocity information assets that require new forms of processing in order to enhance decision-making, lead to insights, and optimize business processes

A

Big Data

61
Q

Big Data generally consists of what four things?

A
  1. Traditional enterprise data
  2. Machine-generated/sensor data
  3. Social data
  4. Images
62
Q

Big Data has three distinct characteristics:

A
  1. Volume
  2. Velocity
  3. Variety
63
Q

Velocity in big data refers to the fact that the rate of which data flows into an organization is rapidly (increasing/decreasing).

A

increasing

64
Q

Why is velocity critical?

A

It increases the speed of the feedback loop between a company, its customers, its suppliers, and its business partners

65
Q

Big Data formats change (slowly/rapidly).

A

rapidly

66
Q

What are the three issues with Big Data?

A
  1. Big data can come from untrusted sources
  2. Big Data is dirty
  3. Big Data changes, especially in data streams
67
Q

refers to inaccurate, incomplete, incorrect, duplicate, or erroneous data

A

dirty data

68
Q

What three things have made processing Big Data today affordable for most organizations?

A
  1. Hardware
  2. Cloud computing
  3. Open-source software
69
Q

What is the first step for many organizations toward managing data?

A

integrate information silos into a database environment and then to develop data warehouses for decision making

70
Q

an information system that does not communicate with other related information systems in an organization

A

information silos

71
Q

What type of databases are particularly useful when working with Big Data?

A

NoSQL

72
Q

the coordinated processing of an application by multiple processors that work on different parts of the application, with each processor utilizing its own operating system and memory

A

massively parallel processing

73
Q

a database management system that primarily relies on main memory for data storage, in contrast to DBMSs that use hard -drive storage

A

in-memory database

74
Q

refers to the storage or relatively inactive data that does not have to be accessed frequently or rapidly

A

cold data

75
Q

refers to data that must be accessed frequently and rapidly

A

hot data

76
Q

What are the 5 strategies that can be used by modern organizations to manage Big Data and gain value from it?

A
  1. Making Big Data Available
  2. Enabling Organizations to Conduct Experiments
  3. Microsegmentation of Customers
  4. Creating New Business Models
  5. Organizations Can Analyze Big Data
77
Q

A/B experiments have only _____ possible outcomes.

A

two

78
Q

dividing customers up into very small groups, or even down to the individual customer

A

microsegmentation

79
Q

Big Data is valuable to various functional areas in the firm. What five functional areas does this include?

A
  1. Human Resources
  2. Product Development
  3. Operations
  4. Marketing
  5. Government Operations
80
Q

applications, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make better decisions

A

business analytics

81
Q

a repository of historical data that are organized by subject to support decision makers within the organization

A

data warehouses

82
Q

Data warehouses are (inexpensive/expensive), so they are used primarily by (small/large) companies.

A

expensive; large

83
Q

a low-cost, scaled down version of a data warehouse that is designed for the end-user needs in a strategic business unit (SBU) or an individual department

A

data mart

84
Q

T or F: Data warehouses can be implemented more quickly than data marts, often in less than 90 days

A

false; data marts can be implemented more quickly

85
Q

T or F: data marts support local rather than central control by conferring power on the user group. typically, groups that need a single or a few business analytics applications require only a data mart rather than a data warehouse.

A

true

86
Q

What are the 6 basic characteristics of data warehouses and data marts?

A
  1. Organized by business dimension or subject
  2. Use online analytical processing
  3. Integrated
  4. Time variant
  5. Nonvolatile
  6. Uses a multidimensional data structure
87
Q

A data warehouse/mart may store _____ of data, while transactional systems maintain _____ data.

A

years; recent

88
Q

What does it mean to say data warehouses and data marts are “nonvolatile”?

A

Users cannot change or update the data

89
Q

Who updates warehouses and marts?

A

Through IT-controlled load processes rather than by users

90
Q

A common representation for this multidimensional structure (which is the structure data is stored in for data warehouses/marts) is the ____ _____.

A

data cube

91
Q

The data in data warehouses and marts are organized by ______ ______, which are subjects such as product, geographic area, and time period.

A

business dimensions

92
Q

What does the Business Analytics Process start with?

A

A business problem, often called pain points by practicing managers.

93
Q

transmission speed

A

bandwidth

94
Q

Transmission speed (bandwidth) in computer networks, particularly the Internet, is rapidly (increasing/decreasing)

A

increasing.

95
Q

Advances in digital storage capacity and access speed are driving the cost of storage (up/down), meaning that what?

A

down; organizations are able to store and analyze huge amounts of data

96
Q

What is the most important issue that you will face in the Business Analytics Process?

A

Defining the business problem

97
Q

an ongoing collection of related activities that create a product or service of value to the organization, its business partners, and its customers

A

a business process

98
Q

What is the next step in the Business Analytics Process after defining the business problem?

A

consider the data that you have for the analysis

99
Q

What is the heart of the analytics process?

A

Big Data

100
Q

What are the 3 types of analytics applications?

A
  1. Descriptive Analytics
  2. Predictive Analytics
  3. Prescriptive Analytics
101
Q

In general, who usually performs descriptive, predictive, and prescriptive analyses?

A

Data scientists

102
Q

What is the most common and popular business analytics tool?

A

Excel

103
Q

the conversion of raw data into a smaller amount of more useful information

A

data reduction

104
Q

Descriptive, predictive, and prescriptive analytics are essentially steps in _____ _______.

A

data reduction

105
Q

Summarizes what has happened in the past and enables decision makers to learn from past behaviors

A

descriptive analytics

106
Q

What are the business analytics tools in descriptive analytics?

A
  1. Online Analytical Processing (OLAP)
  2. Data Mining
  3. Decision Support Systems
107
Q

the process of searching for valuable business information in a large database, warehouse, or mart

A

data mining

108
Q

a data mining application that discovers co-occurrence relationships among activities performed by specific individuals or groups

A

affinity analysis

109
Q

What is this an example of: young men often buy diapers and beer at the same time

A

affinity analysis

110
Q

analysis in which retailers seek to understand the purchase behavior of customers (ex: customers who bought book A might also like to buy book B)

A

market basket analysis

111
Q

simplified representations, or abstractions, of reality

A

models

112
Q

combine models and data to analyze semi structured problems and some unstructured problems that involve extensive user involvement; enable business managers and analysts to access data interactively, to manipulate these data, and to conduct appropriate analyses

A

decision support systems

113
Q

examines how sensitive an output is to any change in an input while keeping other inputs constant

A

sensitivity analysis

114
Q

analysis that attempts to predict the impact of changes in the assumptions– that is, the input data– on the proposed solution

A

what if analysis

115
Q

analysis that attempts to calculate the value of the inputs necessary to achieve a desired level of output

A

goal seeking analysis

116
Q

examines recent and historical data to detect patterns and predict future outcomes and trends. _________ analytics provides estimates about the likelihood of a future outcome

A

predictive analytics

117
Q

What is the difference between preventive maintenance and predictive maintenance?

A

Preventive: scheduled at regular intervals
Predictive: occurs as needed based on conditions of the asset (reduces labor and material costs)

118
Q

a type of predictive analysis; is the process of analyzing opinions expressed in a piece of text (ex: a Tweet) or in a speech to determine whether the writer’s or listener’s attitude toward a particular topic, product, or service is positive, negative, or neutral

A

sentiment analysis

119
Q

T or F: Problems with predictive analytics are most likely to arise when algorithms make things happen automatically, without human intervention or oversight

A

True (think about Uber armed man example)

120
Q

T or F: The best analytics approach depends on the kind of data you’re working with, therefore, there cannot be one best approach for all problems.

A

True

121
Q

recommends one or more courses of action and identifies the likely outcome of each decision

A

prescriptive analytics

Management Information Systems (5 decks)

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