Week 1 Intro to Decision making and Analytics Flashcards

-Recognize what this unit is, and is not, about -Describe the definition of decision making -Explain the importance of decision making -Describe the definition of Analytics -Explain how analytics and decision making interconnect

You may prefer our related Brainscape-certified flashcards:
1
Q

What does ERD stand for?

A

Entity Relationship Diagram

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What tool do you use for Database design?

A

online ERD tools

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What tool do you use for Data Visualization?

A

Tableau

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What has caused an increasing demand of data analytics?

A

web 3.0
since 2010 social media made everyone a data administrator

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What is the definition of Business analytics (BA)?

A

a set of disciplines and technologies for solving business problems using:
-data analysis
-statistical models
-other quantitative methods

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What are the potential business problems?

A

-Production of products and services (Add value!)
-Division of labour, dealing with complexity
-Collaboration of individuals to achieve a greater goal
-Governance and control
-Efficient allocation of resources (input / output)
-Effectiveness (Do the right things > value/quality)
-Efficiency (Do the things right > cost)
-Make a profit!

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is involved with Data analysis?

A

-planning
-data processing
-modeling
-follow up

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What are examples of statistical models?

A

-regression model
-line graph

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are examples of quantitative methods?

A

-SQL
-Tableau
-Excel

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What are the 3 levels of Business Analytics?

A

-descriptive
-predictive
-prescriptive

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What is descriptive analytics?

A

reporting analytics that is retrospective of historic data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What question does descriptive analytics answer?

A

what happened?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What are the 3 enablers of descriptive analytics?

A

-descriptive statistics
-data warehouse
-data visualization

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is predictive analytics?

A

looking at past data to predict the future

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What are predictive analytics enablers?

A

-forecasting
-data mining
-text mining/ web mining

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What is prescriptive anlaytics?

A

uses both descriptive and predictive to create the alternatives,
and then determines the best one

17
Q

What are prescriptive analytics enablers?

A

-optimization
-simulation
-multi-criteria decision modelling
-programming

18
Q

What are the 5 fundamental components of an information system (IS)?

A
  1. Computer hardware
  2. Software
  3. Data
  4. Procedures
  5. People
19
Q

How does IS differ from Information Technology (IT)?

A

IT only includes raw tech such as:
-hardware
-software
-data
hence, IT+people+procedures= IS

20
Q

What is involved in the scientific approach to managerial decision making?

A

-development of a (mathematical) model of a real-world scenario
-model provides insight into the solution of the managerial problem
-decision-making process is not affected by personal bias etc
-commonly referred to as quantitative analysis, management science, or operations
research

21
Q

What are the steps involved in modelling?

A
  1. formulation
  2. solution
  3. interpretation and sensitivity analysis
22
Q

What does data analytics mean?

A

-“the process of inspecting, cleaning,
transforming and modelling data for
business decision making”
- May be viewed as a low-level Data
Science