Exam 1 Flashcards
1
Q
Information age
A
The present time during which infinite quantities of facts or Wylie available to anyone who can use a computer
2
Q
Snapshot
A
A view of data at a particular moment in time
3
Q
What is the chief technology officer responsible for?
A
Ensuring the throughput, speed, accuracy, availability, and reliability of an organizations information technology
4
Q
Information
A
Data converted into a meaningful and useful context
5
Q
Business unit
A
A segment of a company representing a specific business function
6
Q
What is the chief privacy officer responsible for?
A
Ensuring the ethical and legal use of information within a company
7
Q
Business analytics
A
The scientific process of transforming data into insight for making better decisions
8
Q
Many chief privacy officers are what by training?
A
Lawyers
9
Q
Business process
A
A Standardized set of activities that accomplish a specific task, such as processing a customers order
10
Q
Internet of things
A
A world where interconnected Internet enabled devices or things have the ability to collect and share data without human intervention
11
Q
Machine to machine
A
Devices that connect directly to other devices
12
Q
Structured data
A
Stored in a traditional system such as a relational database or spreadsheet. Ex: sensor data, point of sale data, accounting data
13
Q
Unstructured data
A
Data that is not stored in a formal database. Example word processed documents, text messages
14
Q
Big data
A
A collection of large complex data sets, including structured and unstructured data, which cannot be analyzed using traditional database methods
15
Q
What are the five characteristics of big data?
A
Variety
veracity
volume
velocity
value
16
Q
Report
A
A document containing data organized in a table, matrix, or graph allowing users to comprehend and understand info
17
Q
Static report
A
Created once based on data that does not change
18
Q
Dynamic report
A
Changes automatically during creation
19
Q
Business intelligence
A
Information collected from multiple sources such as suppliers, customers, competitors, partners, and industries that analyzes patterns, trends, and relationships for strategic decision making
20
Q
Analytics
A
The science of fact-based decision making
21
Q
Business analytics
A
The scientific process of transforming data into insight for making better decisions
22
Q
Descriptive analytics
A
Techniques that describe part performance and history
23
Q
Predictive analytics
A
Techniques that extract information from data and use it to predict future trends and identify behavioral patterns
24
Q
Prescriptive analytics
A
Techniques that create models including the best decision to make or course of action to take
25
Behavioral analysis
Uses data about peoples behaviors to understand and predict future actions
26
Exploratory data analysis
Identifies patterns in data, including outliers, uncovering the underlying structure to understand relationships between variables
27
Pattern recognition analysis
Classifies or labels an identified pattern in the machine learning process
28
Social media analysis
Analyzes text flowing across the Internet including unstructured text from blogs and messages
29
Speech analysis
Analyzes recorded calls to gather information
30
Text analysis
Analyzes unstructured data to find trends and patterns and words and sentences
31
Web analysis
Analyzes unstructured data associated with websites to identify consumer behavior and website navigation
32
Knowledge
Skills, experience, and expertise coupled with information and intelligence that creates a persons intellectual resources
33
Knowledge worker
Individual valued for their ability to interpret and analyze information
34
Management information systems (MIS)
A business function, like accounting and human resources, which moves information about people, products, and processes across the company to facilitate decision-making and problem-solving
35
Chief data officer
Responsible for determining the types of information the enterprise will capture, retain, analyze, and share
36
Chief Security officer
Responsible for ensuring the security of MIS systems
37
Chief knowledge officer
Responsible for collecting, maintaining, and distributing the organizations knowledge
38
What is the Luddite fallacy?
The simple observation that new technology does not lead to higher overall unemployment in the economy. New technology doesn’t destroy drops it only changes the composition of jobs in the economy
39
What Is porters five forces model?
A model that identifies and analyzes five competitive forces that shape every industry
40
Porters five forces
Buying power, supplier power, threat of substitutes, threat of new entrants, rivalry among existing competitors
41
Organizations typically follow one of Porter’s three generic strategies when entering a new market, which are:
Cost leadership, differentiation, focused strategy
42
Value chain analysis
Views a firm as a series of business processes that each add value to the product or service
43
The difference between cost and value
Margin
44
What are challenges for managerial decision making?
Analyze large amounts of information
apply sophisticated analysis techniques
make decisions quickly
45
The six step decision-making process
Problem identification
data collection
solution generation
solution test
solution selection
solution implementation
46
Structured decisions
Situations where established processes offer potential solutions
47
Managerial decision making
Employees evaluate company operations to identify, adapt to, and leverage change
48
Unstructured decisions
Occurs in situations in which no procedures or rules exist guide decision makers toward the correct choice
49
Strategic decision making
Managers develop overall strategies, goals, and objectives
50
Project
A temporary activity a company undertakes to create a unique product, service, or result
51
Metrics
Measurements that evaluate results to determine whether a project is meeting its goals
52
Critical success factors
The crucial steps companies make to perform to achieve their goals and objectives and implement strategies
53
Key performance indicators
The quantifiable metrics a company uses to evaluate progress toward critical success factors. Examples: turnover rate of employees, number of product returns, number of new customers, average customer spending
54
External key performance indicators
Market share – the portion of the market that a firm captures
55
Internal key performance indicators
Return on investment – indicates the earning power of a project
56
Efficiency MIS metrics
Measure the performance of MIS itself, such as throughput, transaction speed, and system availability
57
Effectiveness MIS metrics
Measures the impact MIS has on business processes and activities, including customer satisfaction and customer conversation rates
58
Benchmark
Baseline values the system seeks to attain
59
Benchmarking
A process of continuously measuring system results, comparing those results to optimal system performance and identifying steps and procedures to improve system performance
60
What is the difference between a structured decision process and an unstructured decision process?
Structured is one for which there is an understood and accepted method, and unstructured is one for which there is no agreed-upon decision making process
61
Transaction processing system
Basic business system that serves the operational level and assists in making structure decisions
62
Decision support system
Models information to support managers and business professionals during the decision-making process
63
Executive information system
A specialized DSS that supports senior level executives within the organization
64
What does CRUD stand for within the transaction processing system?
Create, read, update, and delete
65
Analytical information
Encompasses all organization information and its primary purpose is to support the performing of managerial analysis or semistructured decisions
66
Online analytical processing
Manipulation of information to create business intelligence in support of strategic decision making
67
Sensitivity analysis
The study of the impact that changes in one or more parts of the model have on other parts of the model
68
Goal seeking analysis
Find the input necessary to achieve goals such as a desired level of output
69
Optimization analysis
An extension of goal seeking analysis, finds the optimum value for a target variable by repeatedly changing Other variables, subject to specified constraints
70
What are the four quantitative models used by DSSs?
Input, process, output, feedback
71
How are the transaction processing system and decision support system related?
The TPS supplies transaction based data to the DSS
72
What is an executive information system?
Specialized DSS that support senior-level executives within the organization. Characteristics are granularity, visualization, and digital dashboard
73
The executive information system needs information from what to help executives make decisions?
The transaction processing systems
74
Drill-down
Enables users to get details, and details of details, of information
75
Slice-and-dice
Looks at information from different perspectives
76
Pivot
Rotates data to display alternative presentations of the data
77
Expert systems
Computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems
78
Generic algorithm
An artificial intelligence system that mimics the revolutionary survival of the fittest process to generate increasingly better solutions to a problem
79
Case-based reasoning
A method whereby new problems are solved based on the solutions from similar cases solved in the past
80
Mutation
The process within a genetic algorithm of randomly trying combinations and evaluating the success or failure of the outcome
81
What are some examples of AI?
Automation, complex analytics, fraud detection, resource scheduling
82
Machine learning
A type of artificial intelligence that enables computers to both understand concepts in the environment and also to learn
83
Data augmentation
Occurs when adding additional training examples by transforming existing examples
84
What is overfitting and underfitting?
Over fitting is when the machine learning model matches the training data so closely that the model fails to make correct predictions. Unfitting occurs when a machine learning model has poor predictive abilities because it did not learn the complexity in the training data
85
Sample bias
Occurs when using incorrect training data to train the machine
86
Prejudice bias
Occurs as a result of training data that is influenced by cultural or other stereotypes
87
Measurement bias
Occurs when there is a problem with the data collected that skews the data in One Direction
88
Variance bias
A mathematical property of an algorithm. This is the only bias not associated with the input or training data. Models are sensitive to noise
89
Neural network
Attempts to emulate the way the human brain works
90
Fuzzy logic
Mathematical method of handling imprecise or subjective information
91
Reinforcement learning
The training of machine learning models to make a sequence of decisions
92
Haptic interface
Uses technology allowing humans to interact with a computer through bodily sensations and movements
93
Customer facing process
Results in a product or service that is received by an organizations external customer
94
Business facing process
Invisible to the external customer but essential to the effective management of the business
95
Business process mapping
The activity of creating a detailed flow chart or process map of a work process showing its inputs, tasks, and activities in a structured sequence
96
Business process model
Graphic description of a process showing the sequence of process tasks which is developed for a specific model
97
As-is process model
Represents the current state of the operation that has been mapped without any specific improvements or changes to existing processes
98
To-be process model
Shows the results of applying change improvement opportunities to the current (as-is) process model
99
Workflow
Includes the tasks, activities, and responsibilities required to execute each step in a business process
100
Workflow control systems
Monitor processes to ensure tasks, activities, and responsibilities are executed as specified
101
Digitization
The automation of existing manual and paper-based processes and workflows to a digital format
102
Operationalized analytics
Makes analytics part of a business process
103
Business process improvement
Attempts to understand and measure the current process and make performance improvements accordingly
104
Robotic process automation
Do use of software with artificial intelligence and machine learning capabilities to handle high volume, repeatable tasks that previously required a human to perform
105
Machine vision
The ability of a computer to see by digitizing an image, processing the data contains, and taking some kind of action
106
Business process reengineering
The idea that radical redesign and re-organization of an enterprise (wiping the slate clean) sometimes was necessary to lower costs and increase quality of service. Also that information technology was the key enabler for change
107
Data mining
The process of analyzing data to extract information not offered by the raw data alone
108
What are the three elements of data mining?
Data, discovery (new patterns), deployment (implementing discoveries)
109
Data Profiling
The process of collecting statistics and information about data in an existing source
110
Data replication
The process of sharing information to ensure consistency between multiple data sources
111
Recommendation engine
A data mining algorithm that analyzes a customers purchases and actions on a website and then uses the data to recommend complementary products
112
Classification
Assigns records to one of a predefined set of classes
113
Estimation
Determines values for an unknown continuous variable behavior or estimated future value
114
Affinity grouping
Determines which things go together
115
Clustering
Segments a heterogeneous population of records into a number of More homogenous subgroups
116
Data mining prediction
A statement about what will happen or might happen in the future like predicting future sales or employee turnover
