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EXAM B ITM 310 Flashcards

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1
Q

attribute

A

Each characteristic or quality of a particular entity.

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2
Q

big data

A

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

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3
Q

bit

A

A binary digit—that is, a 0 or a 1.

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4
Q

business rules

A

Precise descriptions of policies, procedures, or principles in any organization that stores and uses data to generate information.

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5
Q

byte

A

A group of eight bits that represents a single character.

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6
Q

database management system (DBMS)

A

The software program (or group of programs) that provide access to a database.

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7
Q

data dictionary

A

A collection of definitions of data elements; data characteristics that use the data elements; and the individuals, business functions, applications, and reports that use these data elements.

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8
Q

data file (also table)

A

A collection of logically related records.

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9
Q

data governance

A

An approach to managing information across an entire organization.

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10
Q

data lake

A

A central repository that stores all of an organization’s data, regardless of their source or format.

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11
Q

data mart

A

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 a department.

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12
Q

data model

A

A diagram that represents entities in the database and their relationships.

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13
Q

data silo

A

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

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14
Q

data warehouse

A

A repository of historical data that are organized by subject to support decision makers in the organization

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15
Q

entity

A

Any person, place, thing, or event of interest to a user.

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16
Q

entity relationship (ER) diagram

A

Document that shows data entities and attributes and relationships among them.

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17
Q

entity relationship (ER) modeling

A

The process of designing a database by organizing data entities to be used and identifying the relationships among them.

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18
Q

explicit knowledge

A

The more objective, rational, and technical types of knowledge.

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19
Q

field

A

A characteristic of interest that describes an entity.

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20
Q

foreign key

A

A field (or group of fields) in one table that uniquely identifies a row (or record) of another table.

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21
Q

functional dependency

A

A means of expressing that the value of one particular attribute is associated with, or determines, a specific single value of another attribute.

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22
Q

instance

A

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

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23
Q

intellectual capital (or intellectual assets)

A

other terms for knowledge

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24
Q

joint operation

A

A database operation that combines records from two or more tables in a database.

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25
knowledge management (KM)
A process that helps organizations identify, select, organize, disseminate, transfer, and apply information and expertise that are part of the organization’s memory and that typically reside within the organization in an unstructured manner.
26
Knowledge management systems (KMS)
Information technologies used to systematize, enhance, and expedite intra- and interfirm knowledge management.
27
master data
A set of core data, such as customer, product, employee, vendor, geographic location, and so on, that spans an enterprise’s information systems.
28
master data management
A process that provides companies with the ability to store, maintain, exchange, and synchronize a consistent, accurate, and timely “single version of the truth” for the company’s core master data
29
multidimensional structure
Storage of data in more than two dimensions; a common representation is the data cube.
30
normalization
A method for analyzing and reducing a relational database to its most streamlined form to ensure minimum redundancy, maximum data integrity, and optimal processing performance.
31
primary key
A field (or attribute) of a record that uniquely identifies that record so that it can be retrieved, updated, and sorted.
32
query by example
To obtain information from a relational database, a user fills out a grid or template—also known as a form—to construct a sample or a description of the data desired.
33
record
A grouping of logically related fields.
34
relational database model
Data model based on the simple concept of tables in order to capitalize on characteristics of rows and columns of data.
35
relationships
Operators that illustrate an association between two entities.
36
secondary key
A field that has some identifying information, but typically does not uniquely identify a record with complete accuracy.
37
structured data
Highly organized data in fixed fields in a data repository such as a relational database that must be defined in terms of field name and type (e.g., alphanumeric, numeric, and currency).
38
structured query language
The most popular query language for requesting information from a relational database.
39
table
A grouping of logically related records.
40
tactic knowledge
The cumulative store of subjective or experiential learning, which is highly personal and hard to formalize.
41
transactional data
Data generated and captured by operational systems that describe the business’s activities, or transactions.
42
unstructured data
Data that do not reside in a traditional relational database.
43
accountability
A tenet of ethics that refers to determining who is responsible for actions that were taken.
44
code of ethics
A collection of principles intended to guide decision making by members of an organization.
45
digital dossier
An electronic description of an individual and his or her habits.
46
electronice surveillance
Tracking people’s activities with the aid of computers.
47
ethics
The principles of right and wrong that individuals use to make choices to guide their behaviors.
48
information privacy
The right to determine when, and to what extent, personal information can be gathered by or communicated to others.
49
liability
A legal concept that gives individuals the right to recover the damages done to them by other individuals, organizations, or systems.
50
opt in model
A model of informed consent in which a business is prohibited from collecting any personal information unless the customer specifically authorizes it.
51
opt out model
A model of informed consent that permits a company to collect personal information until the customer specifically requests that the data not be collected.
52
privacy
The right to be left alone and to be free of unreasonable personal intrusions.
53
privacy policies
An organization’s guidelines for protecting the privacy of customers, clients, and employees.
54
profiling
The process of forming a digital dossier.
55
responsibility
A tenet of ethics in which you accept the consequences of your decisions and actions.
56
_________ issues involve collecting, storing, and disseminating information about individuals.
privacy
57
Companies prefer the _________ model of informed consent.
opt out
58
The _________ approach posits that ethical actions treat all human beings equally, or, if unequally, then fairly, based on some defensible standard.
fairness
59
Smartphones are sensors that can be used for electronic surveillance.
true
60
The ________ key is an identifier field that uniquely identifies a record.
primary
61
Knowledge is information in action.
true
62
Data warehouses and data marts are multidimensional.
true
63
Organizations can use Big Data to create new business models.
true
64
Data marts support the development of one or a few related analytics applications.
true
65
________ analytics drives the coupons you get at the grocery store when you use your loyalty card.
predictive
66
Predictive analytics require prescriptive analytics with two additional components: actionable data and a feedback system that tracks the outcome produced by the action taken.
false
67
Google’s translation app uses ___.
natural language processing
68
Artificial intelligence is superior to natural intelligence regarding ________.
preservation of knowledge
69
________ refers to the ability of information systems to identify objects, scenes, and activities in images.
computer vision
70
___ helps predict fraud.
machine learning
71
business analytics (BA)
The process of developing actionable decisions or recommendations for actions based on insights generated from historical data.
72
business intelligence
A broad category of applications, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make more informed decisions.
73
dashboard
A business analytics presentation tool that provides rapid access to timely information and direct access to management reports.
74
data mining
The process of searching for valuable business information in a large database, data warehouse, or data mart.
75
decision making
A choice that individuals and groups make among two or more alternative
76
decision support systems (DSSs)
Business intelligence systems that combine models and data in an attempt to solve semistructured and some unstructured problems with extensive user involvement.
77
descriptive analytics
A type of business analytics that summarize what has happened in the past and allow decision makers to learn from past behaviors.
78
geographic information system (GIS)
A computer-based system for capturing, integrating, manipulating, and displaying data using digitized maps.
79
management
A process by which organizational goals are achieved through the use of resources.
80
online analytical processing (OLAP) or multidimensional data analysis
A set of capabilities for “slicing and dicing” data using dimensions and measures associated with the data.
81
predictive analytics
A type of business analytics that examines recent and historical data in order to detect patterns and predict future outcomes and trends.
82
prescriptive analytics
A type of business analytics that recommend one or more courses of action and showing the likely outcome of each decision.
83
productivity
The ratio between the inputs to a process and the outputs from that process.
84
data reduction
Data reduction is the conversion of raw data into a smaller amount of more useful information. Descriptive, predictive, and prescriptive analytics are essentially steps in data reduction.
85
Fill in the blank: You should always want your audience to know or ______ something.
do
86
Many presenters believe their audience knows better than them, and should choose whether to act on information presented.
true
87
When giving a presentation, only present supporting data, and let the audience find their own data that contradicts what you are presenting.
true
88
Do you want to present to the widest possible audience or a specific audience?
specific
89
The best way to start your story board is to mock up your whole presentation with presentation software.
false

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