Study Guide

Learning outcomes

The student is able to
- use planning, analysis and decision-making tools and techniques in strategic planning
- analyze financial statements and business reports and use them as a basis for decisions
- make business decisions in various business contexts
- apply data in decision making

Teaching methods

•Lecturing in TEAMS
•Group Discussion
•Individual Assignment
•Individual or Group Project Task for Analysis based on the intake of students
•A multiple choice question examination at the end of the study unit based on the concepts studied during the
study unit.

Location and time

The location of lessons will be in Zoom.
IF ANY CHANGES, STUDENTS WILL BE INFORMED IN ADVANCE

Learning materials and recommended literature

All the materials for learning will be uploaded in the Canvas.

Alternative completion methods of implementation

You can complete the study unit virtually:
• Follow the instructions in CANVAS
• Submit the assignments on time
• Attend the project task evaluation and multiple choice examination without any fail
• You can complete the study unit successfully.

Important dates

The course will begin on 19.08.2024 and ends on 31.12.2024
The online sessions are on the following dates:
Date and Time:
03.09.2024 16.00 - 18.00 Tuesday
10.09.2024 16.00–18.00
17.09.2024 16.00–18.00
24.09.2024 16.00–18.00
15.10.2024 16.00–18.00
30.10.2024 16.00–18.00

Forms of internationality

The topics you are learning out of the study unit are the basic to business intelligence.

Students workload

basic work load

Content and scheduling

Scheduling: There will be 6 online sessions of 2 hours each, out of which 5 session will be teaching session and the last few session are for project evaluation, feedback and
comments.
Content:
Module 1: Introduction to DDDM
- WHAT IS DDDM?
- Algorithm to make DDDM
- Data Identification and Application
Module 2:Technology and Types of Data
• The marketplace and emerging trends in big data analytics
• Business impacts of technology advancements and data trends
• What is Big Data?
• Identifying, organizing, and processing data
• Structured", "Semi-Structured", and "Unstructured" data
• Implications of unstructured data - Case studies
• Data tools and technologies
Module 3: Data Analysis Techniques and Tools
•Types of data analysis techniques
•The role of Excel
•The role of SAS
• The role of R
• The role of Python
• The Power of Visualization
• The role of QlikView
• Data analysis approaches and techniques
• A Business Example of Data Visualization Tools
Module 4: Data-Driven Decision-Making Project
The course project will give you an opportunity to practice what you have learned. You will participate in a simulated business situation in which you will select the best course of action. You will then prepare a final deliverable, which will be evaluated by your peers. Additionally, you will have the opportunity to provide feedback on your peer's submissions.

Further information for students

The objective of the study unit is
* Overview of Data Driven Decision Making
* Defining the Problem
* Analyzing and Understanding the data
* Evaluating the alternatives
* Communicating the decision

Grading scale

H-5

Evaluation methods and criteria

Assignment-20
Project Evaluation (50)
Examination (30)
Total -100

Evaluation criteria, fail (0)

If the marks are less than 40, the student will fail for the study unit

Evaluation criteria, satisfactory (1-2)

If the marks between 40-60, the grade will be 1 and 2
ie; 40-49 will get 1
50-59 will get 2

Evaluation criteria, good (3-4)

If the marks between 60-80, the grade will be 3 and 4
ie; 60-69 will get 2
70-79 will get 3

Evaluation criteria, excellent (5)

If the marks between 80-100, the grade will be 4 and 5
ie; 80-89 will get 4
90-100 will get 5