WHU: DSS > Session 1 > Flashcards

Session 1 Flashcards

(46 cards)

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1
Q

Simon’s decision making model: what does management equal?

A

decision making

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2
Q

what is bounded rationality?

A

rationality is limited when humans make decisions, thus they will select a satisfactory rather than optimal deicsion

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3
Q

How do humans make decisions?

A

the consciously or subconsciously follow a sytsmeatic decision-making process

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4
Q

what are the fice aspects in Simon’s model?

A
  1. intelligence
  2. design
  3. choice
    4 (+) implementation
  4. (+) monitoring
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5
Q

what is the first phase in simon’s model? What is its output?

A
  1. intelligence phase:
    - problem identification
    - problem ownership
    - classification
    - decomposition
    –> this gives us a problem statement
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6
Q

what is the second phase in simon’s model? what is its output?

A
  1. design phase
    - model formulation
    - selecting criteria for choice
    - searching for alternative
    - measuring outcomes
    –> this gives us alternatives
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7
Q

what is the third phase in simon’s model?

A
  1. choice phase
    - selection of best alternatives
    - solution to the model
    - sensistivity analysis
    - plan for implementation
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8
Q

how does the model flow?

A
  • failure might bring us back to the previous stage
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9
Q

what is important in the intelligence phase?

A
  1. differentiate between problems and symptoms
  2. establish problem ownership
  3. classify problems (as often problems are repeated)
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10
Q

what does simon say about where the difficulty of decision-making lies?

A

it centres around the degrees of uncertainty that relate to the decision and the gaps in out knowledge

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11
Q

what is the definition of DSS (know it by heart)

A

decision support systems are interactive computer-based systems which support decision makes by utilization of data and models to solve un- or semi-strcutured problems

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12
Q

what are the 6 componenets every definition of DSS should have

A
  1. interactive computer based systems
  2. decision makers
  3. decision support
  4. data
  5. models
  6. decision problems
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13
Q

what are Simon’s three degrees of structuredness?

A
  1. highly structures (programmed)
  2. semi-structured
  3. highly unstructured
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14
Q

what are anthony’s three types of control?

A
  1. strategic planning (top-level, long-range)
  2. management control (tactical planning)
  3. operational control
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15
Q

what are unstructured decisions?

A

the decision maker must provide judgement, evaluation and insights into the problem definition

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16
Q

what are structured decisions?

A

repetitive and routine decisions where decisions systems can follow a deifinite procedure for handling them to be efficient

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17
Q

what are components of DSS? (model)

A

data management
model management
external models
knowledge based subsystems
user interface

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18
Q

how do decision makers differ?

A
  • how they think and react to problems
  • how they proceed when making deicisons
  • decision making styles
  • organizational level
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19
Q

what is three reasons for errors in decision making?

Study These Flashcards
A
  • decisions from the gut, as the environment can change
  • personal factors (over or under confidence)
  • people are poor in estimating probabilities (we overestimate low probabilities and we underestimate high probabilities)
20
Q

what is a data warehouse?

Study These Flashcards
A

a collection of databases storing current and historical data -> single version of truth
-> no department can directly access it
-> instead business applications are built on the warehouse and may be assessed by different users

21
Q

what are the five main components of the data warehousing process

Study These Flashcards
A
  1. data source (ERP, legacy etc)
  2. ETL process (data gets extracted, transformed, cleansed to get ready for loading into DW)
  3. metadata (gives info about other data)
  4. datamarts (departmental small scale DWs)
  5. API / middleware tools (applications that aneble to access teh data warehouse)
22
Q

what are the two different types of data marts?

Study These Flashcards
A
  1. dependent: subset that is created directly from a DW
  2. independent: a small DW designed for a strategic business unit or a department
23
Q

what is the picture/ model of the data warehousing process?

24
Q

when is it important to distinguish between OLTP and OLAP?

Study These Flashcards
A

when analyising data in a DW: two types of data processing

25
what is OLTP?
online transaction processing: efficient sacing and actualization of transaction data (focus on data processing) -> to carry out day-to-day business functions (e.g., company's checkput system)
26
what is OLAP?
online analytical processing: data analysis of multiple systems at the same time --> to support decision making and to provide answers for business and management queries (dashboard analysis trends in the sales of last year)
27
what are the two ways to represent data used for OLAP?
1. Gables 2. Cubes
28
what is the OLAP operation: Slice?
we cut in one direction: we take a subset of data corresponding to a single value set for one or two dimensions not in the subset --> only filter to see the product 1 sales across time and regions
29
what is the OLAP operation: dice?
cut on more than two dimensions --> only look for product 1 and region 2 sales
30
what is the OLAP operation: drill down/ up?
Down: navigating among levels of data ranging from the most summarized to the most detailed --> from yearly sales to monthly sales Up: vice versa
31
what is the OLAP operation: roll up?
computing all of the data relationships for one or more dimensions --> first look at sales data from each store, than aggregate them according to their regions and then to their countries
32
what is the OLAP operation: Pivot?
change the dimensional orientation of a report or an ad hoc query page display --> change columns and rows
33
what is business analytics?
the process of transofriming data into insights to imrpove business decisions
34
what are the three main functions of business analytics?
1. descriptive: presenting a well-definded business problem and opportunities 2. predictive: giving accuarete projections of future events and outcomes 3. prescriptive: presenting possible business decisions and actions
35
what is data mining?
a process that used statistical, mathematical and AI techniques to extract and identify useful information and subsequent knowledge from large data bases --> data mining goes from finding simple patterns ind at a to inferring rules / models from them
36
what three types of patterns are there?
1. association - link analysis, sequence analysis (what doe ppl buy in sequence) 2. prediction - classification, regression, time series 3. segmentation - clustering (low income, high income)
37
what are the two learning types?
1. supervised learning: classifying data and making predictions based on known classes (you already know some outcomes to build a model) 2. unsupervised learning: trying to understand relationships within datasets based on unknown classes: we don't know which outcomes we will have in the end
38
what is data science?
covers the practical application of advanced analytics, statistics, machine learning and the necessary data prepartion in a business context
39
what is the definition for AI?
AI is the study of how to make computer do thing at which at the moment people are better (but chess computers are better than humans now, meaning it is not AI anymore)
40
is there a suitable definition for AI?
no, as chess computers are better than humans now, meaning it is not AI anymore
41
what is the turing test?
find out if the other opponent is human or a computer by asking questions for 25 minutes
42
what is weak AI?
developed for certain domains only (alex, chess bot etc.)
43
what is strong AI?
developed for being better than humans on various domains and to solve all kinds of problems (like chatgpt, but we are still not there yet)
44
what are the three types of AI?
1. assisted AI: AI which helps humans to perform tasks more efficiently or accurately (lane assistant) 2. augmented AI: uses ML and depp learning to provide humans with actionable data 3. autonomous AI: comprehends its environments, makes decisions and improves strategies based on outcomes (completely self-driven cars)
45
what is machine learning?
- it is a subfield of AI - machine takes data and learns for itself (amazon, google etc.)
46
what is deep learning?
- subset of machine learning - machine furthermore taps into neural networks that simulate human learning and decision-making
WHU: DSS
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