Data-Driven Decision Making - C207 Question and
answers correctly solved 2025/2026
1
. Define analyticsTurning information into knowledge and
developing fact based strategies to gain
2 a competitive edge.
Descriptive/Diag- Encompasses the set of techniques that
. describes what has happened in the past.
nostic analytics
3. Predictive 9. Nominal data*
analyt-ics
4. Prescriptive
ana-lytics
5. Three
character-istic
of big data
6. Davenport-
Kim Three-
Stage Model*
7. Categorical
or discrete
data
variables
8. There are two
types of
categor-ical
data
1/
63
,Consists of techniques that ng results (Communicating and acting on the results)
use models constructed
from past data to predict Represents types of data that can be divided into groups or
the future or ascertain the
categories. Example: race, sex, age group, and educational
impact of one variable on
another.
level, happy, etc.
Decision models that indicate
the best course of action to Nominal and Ordinal
take.
1. Structured and
unstructured large volumes
2. Analytics is used to
discover and communicate
meaningful patterns
3. Analysis of big data
requires a system of
organization
A decision-making model
developed by Thomas
Davenport and Jinho Kim
that consists of three
stages:
1. Framing the
problem, (why are you
trying to do this and what
do we already know)
2. Solving the problem
(Choosing the model,
collecting the data,
analyzing the model)
3. Communicati
2/
63
,Data-Driven Decision Making - C207
Identifies, groups, or categories only. Data cannot be arranged in an
ordering scheme. They are used to name or label a series of values.
Examples, names, pass/fail, gender, race, the color of the eye
Data can not be ordered and makes no sense to calculate means or
standard deviations ott this.
10. Ordinal data* Data is placed into some order by some quality. They are usually non-
numeric
captions like happiness or discomfort. It is the ORDER that matters.
They provide good information about the order of values, like a
customer satis-faction survey.
Examples: top ten best cities to live in or top 10 college football
teams. (ordinal-order matters)
11. Numerical or They can accept any value and can measure nearly anything. Height,
continuous weight, BP, etc...
vari-ables
12. Two types of
Interval and Ratio
nu-merical
data
13. Interval data* It has an order to it and has equal intervals apart.
It gives us the order of values with the ability to quantify the ditterence
between each one.
Ditterences between values can be found and meaningful, but they DO
NOT have a true 0. ( no temperature, no true 0 time, or no true 0 dress
size)
3/
63
, These can be added or subtracted but not multiplied
4/
63
answers correctly solved 2025/2026
1
. Define analyticsTurning information into knowledge and
developing fact based strategies to gain
2 a competitive edge.
Descriptive/Diag- Encompasses the set of techniques that
. describes what has happened in the past.
nostic analytics
3. Predictive 9. Nominal data*
analyt-ics
4. Prescriptive
ana-lytics
5. Three
character-istic
of big data
6. Davenport-
Kim Three-
Stage Model*
7. Categorical
or discrete
data
variables
8. There are two
types of
categor-ical
data
1/
63
,Consists of techniques that ng results (Communicating and acting on the results)
use models constructed
from past data to predict Represents types of data that can be divided into groups or
the future or ascertain the
categories. Example: race, sex, age group, and educational
impact of one variable on
another.
level, happy, etc.
Decision models that indicate
the best course of action to Nominal and Ordinal
take.
1. Structured and
unstructured large volumes
2. Analytics is used to
discover and communicate
meaningful patterns
3. Analysis of big data
requires a system of
organization
A decision-making model
developed by Thomas
Davenport and Jinho Kim
that consists of three
stages:
1. Framing the
problem, (why are you
trying to do this and what
do we already know)
2. Solving the problem
(Choosing the model,
collecting the data,
analyzing the model)
3. Communicati
2/
63
,Data-Driven Decision Making - C207
Identifies, groups, or categories only. Data cannot be arranged in an
ordering scheme. They are used to name or label a series of values.
Examples, names, pass/fail, gender, race, the color of the eye
Data can not be ordered and makes no sense to calculate means or
standard deviations ott this.
10. Ordinal data* Data is placed into some order by some quality. They are usually non-
numeric
captions like happiness or discomfort. It is the ORDER that matters.
They provide good information about the order of values, like a
customer satis-faction survey.
Examples: top ten best cities to live in or top 10 college football
teams. (ordinal-order matters)
11. Numerical or They can accept any value and can measure nearly anything. Height,
continuous weight, BP, etc...
vari-ables
12. Two types of
Interval and Ratio
nu-merical
data
13. Interval data* It has an order to it and has equal intervals apart.
It gives us the order of values with the ability to quantify the ditterence
between each one.
Ditterences between values can be found and meaningful, but they DO
NOT have a true 0. ( no temperature, no true 0 time, or no true 0 dress
size)
3/
63
, These can be added or subtracted but not multiplied
4/
63
