mis k201 Flashcards
provides views of business operations
business intelligence
skill in using productivity software
computer literacy
ubiquitous computing
internet of things
3d and 4d printing
computing trends
searching data to discover relationships to make recommendations
data mining
uses models to display data
data scientist
SQL, access, oracle
database management system
-microsoft access (small)
-oracle (large)
DBMS examples
Machinery
Manpower
Materials
Money
4 resources model
(4 M’s of managing resources)
levels the playing field with small businesses
Impact of Internet (on small business)
understanding the role of information in using business intelligence
information literacy
- data
- database
- process
- information
information systems (IS) and SISs major components
internet, computer networks, database systems
information technologies
using technology to make transportation of goods more efficient
logistics
integration of hardware and software technologies
management information systems (MIS)
oversee networks and cybersecurity
network administrator
analyze business position in marketplace
porter’s five forces model (purpose)
- 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)
Porter’s Five Forces
- overall cost leadership
- differentiation
- focus – market segments
porter’s three strategies
point of sale
POS transaction
attached to items for tracking
RFID
big picture, long term goals
strategic information system (SISs)
responsible for design of information systems
systems analyst
focus on data collection (used for cost reduction)
- minimal human involvement
transaction processing systems (TPS)
arithmetic (+,-,*, /) and comparison (<,=,>)
arithmetic logic unit (ALU)
- word-processing
- spreadsheet
- database
- graphics
- desktop-publishing
-financial planning and accounting
application software
01011100101 (0 & 1’s create language on computer)
binary code
byte, kilo, mega, giga, tera, peta, exa
byte
heart of the computer
central processing unit (CPU)
- 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
- arithmetic
- logical/comparison
- storage and retrieval
computer operation (tasks)
- vacuum tube
- parallel processing
- integrated circuits
- miniaturization
hardware generation names
- main memory devices
- secondary memory devices
memory device (types)
OneDrive
network attached storage
a programming style that organizes software around objects that contain data and code
object oriented programming (OOP)
- swift
- C#
- Java
OOP popular programming languages
windows
operating system (OS)
soft copy - on screen
hard copy - solid
output devices
speed
accuracy
strorage and retrieval
power of computers
(3)
temporary storage vs permanent storage
RAM vs ROM
- application
- database
- disk
- file
- remote access
- web
server platforms
faster retrieval for data and booting
solid state drive (SSDs)
saving vs recalling
storage vs retrieval
forward looking > what is going to happen
business analytics (BA)
future vs past
BA (business analytics) vs BI (business intelligence)
- descriptive (reviews past)
- predictive (decision maker for future)
- prescriptive (recommends action and shows outcome)
Business analytics (BA) methods
- web analytics
- mobile analytics
business analytics common terms
Volume
Variety
Velocity
Veracity
Value
big data five dimensions (the 5 Vs)
data stored in a central location
Data lake
how data is organized
data model
smaller version of a data warehouse
data mart
- data structure
- operations
- integrity rules
data model components
- hierarchical
- network
- relational
- object oriented
data model types
collection of data from a variety of sources
data warehouse
- subject oriented
- integrated
- time variant
- type of data
- purpose
data warehouse characteristics
- input
- ETL (extraction transformation loading)
- storage
- raw data
- summary data
- metadata - output
- data mining analysis
- text mining analysis
data warehouse configuration
- internal
- external
database - types of data
design and management
database administrator (DBA)
software for creating / storing data
(DBMS) database management system
- database engine
- data definition
- data manipulation
- application generation
- data administration
DBMS components
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)
retrieve
reuse
revise
retain
CBR 4 R’s
knows where you are
contextual computing
work with data warehouse
detect trends and discover information and relationships among data items that were not readily apparent
data - mining agents
generate information by using data, models, and well defined algorithms, but expert systems work with heuristic data
decision support system
mimic human thought and behavior in a specific area that human experts have addressed successfully
expert systems
explains to users how solutions were derived
explanation facility
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
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
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)
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
similar to the model bare component
uses techniques such as forward and backward chaining to manipulate a series of rules
inference engine
- demographics
- psychographics
database marketing
segmentation of customers
- CLTV (customer lifetime value)
- RFM (recency, frequency, monetary analysis)
- customer communication (increase loyalty)
- analytical software (monitors customer behavior)
database marketing
tasks of successful campaign
- field (column)
- record (row)
- file (group)
database system structure (data hierarchy)
stores data on multiple servers
distributed database management system (DDBMS)
- fragmentation (how tables are divided)
- replication (stores copies of data)
- allocation (combines the ones above)
DDBMS setup approaches
grouping objects in a class
encapsulation
- physical view
- logical view
logical database design
eliminates redundant data
normalization
- SQL (structured query language)
- QBE (query by example)
data manipulation query languages
- AND (all conditions met)
- OR (one condition met)
- NOT (no conditions met)
QBE operators
- tableau
-power BI
(7 data visualization tools)
visualization platforms
simulates human behavior
Artificial Intelligence (AI)
generating and displaying knowledge and facts
AI is concerned with
- 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)
the so called human machines of AI
augmented intelligence
to complement decision makers
augmented intelligence’s goal
the expert system starts with the goal - the then part - and backtracks to find the right solution
backward chaining
software capable of reasoning and following rule-based processes
-popular in e-commerce
also called
- bots
- virtual agents
- intelligent virtual agents
intelligent agents
- 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
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
similar to a DBMS
used to keep the knowledge base updated
knowledge base management system (KBMS)
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
track and report on computer equipment and network systems to predict when a system crash or failure might occur
monitoring and surveillance agents
was developed so users could communicate with computers in human language
natural language processing (NLP)
perform specific tasks for a user such as remembering information for filling out web forms
personal agents
- 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
help users navigate through vast resources available on the web and provide better results in finding information
shopping and information agents
made of elastomer
- they are simpler to make and less expensive than conventional robots
soft robot
- high speed food handling
- precise pick and place
- warehouse logistics
- advanced assembly
soft robot applications
commonly used in transaction processing systems and management information systems
what-is (decision making analysis)
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)
