Data Analytics (3 cr)
Code: HL00BD67-3001
General information
- Enrollment
-
02.08.2021 - 05.09.2021
Registration for the implementation has ended.
- Timing
-
30.08.2021 - 17.12.2021
Implementation has ended.
- Number of ECTS credits allocated
- 3 cr
- Local portion
- 3 cr
- Mode of delivery
- Face-to-face
- Unit
- School of Business
- Campus
- Main Campus
- Teaching languages
- Finnish
- Seats
- 0 - 37
- Degree programmes
- Bachelor's Degree Programme in Business Management
- Teachers
- Kirsi Marjakoski
- Aki Laaksonen
- Riikka Ahlgren
- Groups
-
ZJA21SHAvoin AMK, lita
-
HTL19S1Liiketalous
-
HTLDIGDigital Business, Business Administration
- Course
- HL00BD67
Evaluation scale
0-5
Content scheduling
The course includes independent familiarization with learning material as well as lectures and exercises and assignments.
Objective
Object of the course
You know the central theoretical concepts and methods of data analytics and business intelligence. You understand how data affects on business.You identify, understand and describe the core business processes. You can collect, modify, interpret and visualize data in order to develop business processes. You use the applicable tools in your tasks.
Course competences
Learning to learn
Learning objectives of the course
You gain skills to utilize data to support business decisions. After completing the course you have knowledge on the possibilites and benefits of using data-analytics in your own field of business.
Content
Business processes and business intelligence. Data sources and methods for collecting, storing, analyzing and visualizing the data. Ethical and transparent utilization of data in business. Using MS PowerBI-software.
Location and time
Schedule 06.09.2021 - 17.12.2021
The course will be implemented as a classroom teaching if covid-10 situation allows.
Materials
EMC Education Services & Services, E. 2015. Data science & big data analytics: Discovering, analyzing, visualizing and presenting data. 1st edition. Indianapolis, Indiana: John Wiley & Sons.
Sedkaoui, S. 2018. Data analytics and big data. Hoboken, New Jersey: ISTE Ltd/John Wiley and Sons Inc.
Teaching methods
Lectures
Literature
Video material
Exercises
Employer connections
Possible company visitors will be confirmed during the course.
Exam schedules
Exam is not included in this course.
Completion alternatives
Accreditation (inclusion)
Recognition of informal learning
Further instructions can be found in the Degree Regulations and in the Bachelor's Degree study guide.
Student workload
Allocation of time on various tasks and student work load in total 81h
Lectures 22h
Independent familiarization with learning material 24h
Exercises and assignments 35h
Assessment criteria, satisfactory (1)
Adequate 1
You know the central principles of data analytics and business intelligence. You know the possibilities of its use in business. You can collect and modify the data. You can use some tools with guidance.
Satisfactory 2
You understand the central principles of data analytics and business intelligence. You understand the possibilities of its use in business. You can collect and modify the data. You use tools somewhat independently.
Assessment criteria, good (3)
Good 3
You apply the principles and tools of data analytics and business intelligence according to business situations. You can collect, modify, interpret and visualize the data. You use applicable tools independently.
Very Good 4
You apply the principles and tools of data analytics and business intelligence according to business situations in order to support decision making. You can develop business based on data.
Assessment criteria, excellent (5)
Excellent 5
You apply the principles and tools of data analytics and business intelligence in business development. You can develop and boost business based on data. You can evaluate and handle the data ethically, critically and according to purpose. You argue the benefits and value of your decisions based on data.
Qualifications
Basics of statistics, basics of spreadsheet calculations.
Further information
Open university of applied sciences 3
The course is mandatory in Digital Business specialization.
The course is recommended to Financial Management specialization students.
The assessment of the course is based on the following credits:
exercises and assignments (100%, 3 ECTS)