Description
Universities often use a Student Information System to manage student data. Such systems may be used both for day-to-day operations (OLTP) and for decision-making and analysis (OLAP).
1. Briefly explain the difference between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) in this context.
2. Give two examples of OLTP operations and two examples of OLAP operations in a university’s student information system.
3. For each example, explain why it fits OLTP or OLAP.
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How can Artificial Intelligence AI help with each step of the decision-making process? Support your answer with an application example, such as HR, marketing, or healthcare.
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Discuss the main assumptions of linear regression (linearity, error independence, error normality, constant variance, and no multicollinearity). Why are these assumptions critical for building valid inferential statistical models?
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Define visual analytics. How does it differ from information visualization, and what questions does each aim to answer in business analytics?
Assignment 1
Deadline: Sunday 28/09/2024 @ 23:59
[Total Mark for this Assignment is 8]
Student Details:
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ID: ###
CRN: ###
Instructions:
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page.
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the question.
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• Use Times New Roman font for all your answers.
Restricted – مقيد
Question One
Pg. 01
Learning
Outcome(s):
CLO3 Recognize
DSS evolution to
the current state
of analytics and
artificial
intelligent.
Restricted – مقيد
Question One
2 Marks
Universities often use a Student Information System to manage student data.
Such systems may be used both for day-to-day operations (OLTP) and for
decision-making and analysis (OLAP).
1. Briefly explain the difference between OLTP (Online Transaction
Processing) and OLAP (Online Analytical Processing) in this context.
2. Give two examples of OLTP operations and two examples of OLAP
operations in a university’s student information system.
3. For each example, explain why it fits OLTP or OLAP.
Question Two
Pg. 02
Learning
Outcome(s):
CLO4 Analyse
various industrial
applications of
DSS and their
limitations.
Restricted – مقيد
Question Two
2 Marks
How can Artificial Intelligence AI help with each step of the decision-making
process? Support your answer with an application example, such as HR,
marketing, or healthcare.
Question Three
Pg. 03
Learning
Outcome(s):
Question Three
2 Marks
CLO1:
Discuss
Demonstrate an
independence, error normality, constant variance, and no multicollinearity). Why
understanding of
are these assumptions critical for building valid inferential statistical models?
the concepts of
decision analysis
and decision
support systems
(DSS) including
probability,
modelling,
decisions under
uncertainty, and
real-world
problems.
Restricted – مقيد
the
main
assumptions
of
linear
regression
(linearity,
error
Question Four
Pg. 04
Learning
Outcome(s):
CLO2 Describe
advanced
Business
Intelligence,
Business
Analytics, Data
Visualization, and
Dashboards.
Restricted – مقيد
Question Four
2 Marks
Define visual analytics. How does it differ from information visualization, and
what questions does each aim to answer in business analytics?
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