Data-driven Decision Making (5 cr)
Code: HL00BQ82-3051
General information
Enrollment
27.11.2023 - 03.12.2023
Timing
24.01.2024 - 24.04.2024
Number of ECTS credits allocated
5 op
Virtual proportion
5 op
Mode of delivery
Distance learning
Unit
Laurea Leppävaara, tiko
Campus
Laurea Virtual Campus
Teaching languages
- English
Seats
20 - 80
Degree programmes
- Tietojenkäsittelyn koulutus, kyberturvallisuus (NKA2), Laurea Leppävaara (Finnish)
- Degree Programme in Business Information Technology, Developing Digital Services (NDA2), Laurea Leppävaara (in Finnish)
Teachers
- Mitha Jose
Teacher in charge
Mitha Jose
Groups
-
NDA222KATietojenkäsittelyn koulutus, digitaalisten palveluiden kehittäminen, monimuotototeutus, K22, Leppävaara
-
NDA223KATietojenkäsittelyn koulutus, digitaalisten palveluiden kehittäminen, monimuotototeutus, K23, Leppävaara
-
NKA222KATietojenkäsittelyn koulutus, kyberturvallisuus, monimuotototeutus, K22, Leppävaara
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 ZOOM
•Group Discussion
•Individual Assignment
•Individual Project Task for decision making
•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 Teams.
https://teams.microsoft.com/l/meetup-join/19%3ameeting_ODQ5ZTg3NzYtY2I5Zi00MGJkLTlmYmYtYzNmNjY3NWIyYmZj%40thread.v2/0?context=%7b%22Tid%22%3a%22f0b9e9d7-8d66-4b16-9c1c-6b07c4796280%22%2c%22Oid%22%3a%22852e1131-503d-4927-9146-6c12fe41a0e7%22%7d
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 24.01.2024 and ends on 27.03.2024
Theonline sessions are on the following dates:
Date and Time:
24.01.2024 16.00 - 18.00
01.02.2024 16.00 - 18.00
07.02.2024 16.00 - 18.00
14.02.2024 16.00 - 18.00
28.02.2024 16.00 - 18.00
13.03.2024 16.00 - 18.00
27.03.2024 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 7 online sessions of 2 hours each, out of which 6 session will be teaching session and the last session is for feedback and comments. All the sessions will be recorded and uploaded to CANVAS for the convenience of students to have access on it in a later time period.
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.
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
The evaluation is based on the following criteria:
Assignment-10
Project Evaluation (40)
Examination (50)
Total -100
Evaluation criteria, fail (0)
If the points are less than 40, the student will fail for the study unit
Evaluation criteria, satisfactory (1-2)
If the points 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 points 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 points between 80-100, the grade will be 4 and 5
ie; 80-89 will get 4
90-100 will get 5