mis k201 Flashcards
(102 cards)
1
Q
provides views of business operations
A
business intelligence
2
Q
skill in using productivity software
A
computer literacy
3
Q
ubiquitous computing
internet of things
3d and 4d printing
A
computing trends
4
Q
searching data to discover relationships to make recommendations
A
data mining
5
Q
uses models to display data
A
data scientist
6
Q
SQL, access, oracle
A
database management system
7
Q
-microsoft access (small)
-oracle (large)
A
DBMS examples
8
Q
Machinery
Manpower
Materials
Money
A
4 resources model
(4 M’s of managing resources)
9
Q
levels the playing field with small businesses
A
Impact of Internet (on small business)
10
Q
understanding the role of information in using business intelligence
A
information literacy
11
Q
- data
- database
- process
- information
A
information systems (IS) and SISs major components
12
Q
internet, computer networks, database systems
A
information technologies
13
Q
using technology to make transportation of goods more efficient
A
logistics
14
Q
integration of hardware and software technologies
A
management information systems (MIS)
15
Q
oversee networks and cybersecurity
A
network administrator
16
Q
analyze business position in marketplace
A
porter’s five forces model (purpose)
17
Q
- buyer power (many options)
- supplier power (few options)
- threat of substitute products or services (other products)
- threat of new entrants (monopoly)
- rivalry among existing competitors (high comp)
A
Porter’s Five Forces
18
Q
- overall cost leadership
- differentiation
- focus – market segments
A
porter’s three strategies
19
Q
point of sale
A
POS transaction
20
Q
attached to items for tracking
A
RFID
21
Q
big picture, long term goals
A
strategic information system (SISs)
22
Q
responsible for design of information systems
A
systems analyst
23
Q
focus on data collection (used for cost reduction)
- minimal human involvement
A
transaction processing systems (TPS)
24
Q
arithmetic (+,-,*, /) and comparison (<,=,>)
A
arithmetic logic unit (ALU)
25
- word-processing
- spreadsheet
- database
- graphics
- desktop-publishing
-financial planning and accounting
application software
26
01011100101 (0 & 1's create language on computer)
binary code
27
byte, kilo, mega, giga, tera, peta, exa
byte
28
heart of the computer
central processing unit (CPU)
29
- machine language (01010)
- assembly language (short codes)
- high level languages (web development)
- fourth generation languages (4GLs) (macrocodes)
- fifth generation languages (5GLs) (uses AI)
computer languages
30
- arithmetic
- logical/comparison
- storage and retrieval
computer operation (tasks)
31
- vacuum tube
- parallel processing
- integrated circuits
- miniaturization
hardware generation names
32
- main memory devices
- secondary memory devices
memory device (types)
33
OneDrive
network attached storage
34
a programming style that organizes software around objects that contain data and code
object oriented programming (OOP)
35
- swift
- C#
- Java
OOP popular programming languages
36
windows
operating system (OS)
37
soft copy - on screen
hard copy - solid
output devices
38
speed
accuracy
strorage and retrieval
power of computers
(3)
39
temporary storage vs permanent storage
RAM vs ROM
40
- application
- database
- disk
- file
- print
- remote access
- web
server platforms
41
faster retrieval for data and booting
solid state drive (SSDs)
42
saving vs recalling
storage vs retrieval
43
forward looking > what is going to happen
business analytics (BA)
44
future vs past
BA (business analytics) vs BI (business intelligence)
45
- descriptive (reviews past)
- predictive (decision maker for future)
- prescriptive (recommends action and shows outcome)
Business analytics (BA) methods
46
- web analytics
- mobile analytics
business analytics common terms
47
Volume
Variety
Velocity
Veracity
Value
big data five dimensions (the 5 Vs)
48
data stored in a central location
Data lake
49
how data is organized
data model
50
smaller version of a data warehouse
data mart
51
- data structure
- operations
- integrity rules
data model components
52
- hierarchical
- network
- relational
- object oriented
data model types
53
collection of data from a variety of sources
data warehouse
54
- subject oriented
- integrated
- time variant
- type of data
- purpose
data warehouse characteristics
55
- input
- ETL (extraction transformation loading)
- storage
- raw data
- summary data
- metadata
- output
- data mining analysis
- text mining analysis
data warehouse configuration
56
- internal
- external
database - types of data
57
design and management
database administrator (DBA)
58
software for creating / storing data
(DBMS) database management system
59
- database engine
- data definition
- data manipulation
- application generation
- data administration
DBMS components
60
is a problem-solving technique
- matches a new case with a previously solved case and its solution (both stored in database)
- offers a solution after searching for a matching case
- a human expert is required to solve the problem if CBR fails to find a match
case based reasoning (CBR)
61
retrieve
reuse
revise
retain
CBR 4 R's
62
knows where you are
contextual computing
63
work with data warehouse
detect trends and discover information and relationships among data items that were not readily apparent
data - mining agents
64
generate information by using data, models, and well defined algorithms, but expert systems work with heuristic data
decision support system
65
mimic human thought and behavior in a specific area that human experts have addressed successfully
expert systems
66
explains to users how solutions were derived
explanation facility
67
the expert system that starts with a series of if-then-else condition pairs is performed
the if condition is evaluated first and then the corresponding then-else action is carried out
forward chaining
68
allows a smooth, gradual transition between human and computer vocabularies and deals with variations in linguistic terms by using a degree of membership
in a conventional set sometimes called a crisp set
fuzzy logic
69
a type of artificial intelligence used mostly to find solutions to optimization and search problems
genetic algorithms can examine complex problems without any assumptions of what the correct solution should be
genetic algorithms (GAs)
70
consist of common sense, rules of thumb, educated guesses, and instinctive judgements, and using heuritic data encourages the application of knowledge based on experience to solve or describe a problem
heuristics
71
similar to the model bare component
uses techniques such as forward and backward chaining to manipulate a series of rules
inference engine
72
- demographics
- psychographics
database marketing
segmentation of customers
73
- CLTV (customer lifetime value)
- RFM (recency, frequency, monetary analysis)
- customer communication (increase loyalty)
- analytical software (monitors customer behavior)
database marketing
tasks of successful campaign
74
- field (column)
- record (row)
- file (group)
database system structure (data hierarchy)
75
stores data on multiple servers
distributed database management system (DDBMS)
76
- fragmentation (how tables are divided)
- replication (stores copies of data)
- allocation (combines the ones above)
DDBMS setup approaches
77
grouping objects in a class
encapsulation
78
- physical view
- logical view
logical database design
79
eliminates redundant data
normalization
80
- SQL (structured query language)
- QBE (query by example)
data manipulation query languages
81
- AND (all conditions met)
- OR (one condition met)
- NOT (no conditions met)
QBE operators
82
- tableau
-power BI
(7 data visualization tools)
visualization platforms
83
simulates human behavior
Artificial Intelligence (AI)
84
generating and displaying knowledge and facts
AI is concerned with
85
- learn and are capable of performing tasks difficult with conventional computers
- used for poorly structured problems
- cannot supply an explanation for the solution
- uses patterns instead of the if-then-else rules used by expert systems
- create a model based on input and output
Artificial neural networks (ANNs)
86
the so called human machines of AI
augmented intelligence
87
to complement decision makers
augmented intelligence's goal
88
the expert system starts with the goal - the then part - and backtracks to find the right solution
backward chaining
89
software capable of reasoning and following rule-based processes
-popular in e-commerce
also called
- bots
- virtual agents
- intelligent virtual agents
intelligent agents
90
- a software package with manual or automated methods for acquiring and incorporating new rules and facts so that the expert system is capable of growth
knowledge acquisition facility
91
similar to a database, in addition to storing facts and figures, keeps track of associated rules and expectations
- tactical knowledge
- heuristic knowledge
- meta knowledge
knowledge base
92
similar to a DBMS
used to keep the knowledge base updated
knowledge base management system (KBMS)
93
process and procedure by which knowledge is gained through experience
several applications
- social media and identifying faces in photos
- recognizing commands spoken into smartphones
- designing intelligent robots
- ANNs
machine learning
94
track and report on computer equipment and network systems to predict when a system crash or failure might occur
monitoring and surveillance agents
95
was developed so users could communicate with computers in human language
natural language processing (NLP)
96
perform specific tasks for a user such as remembering information for filling out web forms
personal agents
97
- perform well at simple, repetitive tasks
- free workers from tedious or hazardous jobs
- typically have limited mobility and some have limited vision
- controlled by a computer program that includes commands
robots
98
help users navigate through vast resources available on the web and provide better results in finding information
shopping and information agents
99
made of elastomer
- they are simpler to make and less expensive than conventional robots
soft robot
100
- high speed food handling
- precise pick and place
- warehouse logistics
- advanced assembly
soft robot applications
101
commonly used in transaction processing systems and management information systems
what-is (decision making analysis)
102
used in decision support systems
- decision makers use it to monitor the effect of a change in one or more variables
what-if (decision making analysis)
