Data-driven Decision Making (5 cr)

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

Location and time

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

Materials

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

Teaching methods

•Lecturing in TEAMS
•Group Discussion
•Individual Assignment
•Individual or Group Project Task for decision making 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.

Exam schedules

The course will begin on19.08.2024 and ends on 31.12.2024
The online sessions are on the following dates:
Date and Time:
22.08.2024 16.00 - 18.00 Thursday
29.08.2024 16.00 - 18.00
05.09.2024 16.00 - 18.00
12.09.2024 16.00 - 18.00
03.10.2024 16.00 - 18.00
17.10.2024 16.00 - 18.00

International connections

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

Completion alternatives

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.

Student workload

basic work load

Content scheduling

Scheduling:
There will be 6 online sessions of 2 hours each, out of which 5 session will be teaching session and the last session is for project evaluation, feedback and comments.
Content:
Module 1: Introduction to DDDM
- WHAT IS DDDM?
- Algorithm to make DDDM
- Regression and Randomized Trials
- 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?
• perspective on big data
• Data and analytics examples
• 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.

Evaluation scale

H-5

Further information

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