Data Analytics (3 cr)

Evaluation scale

0-5

Content scheduling

The course includes independent familiarization with learning material as well as contact lessons 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

The course will be implemented as a classroom teaching.
Lessons are recorded when applicable for the part-time students (IY-group).

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.

Knight, D., Ostrowsky, E., Pearson, M., & Schacht, B. (2022). Microsoft Power BI quick start guide: The ultimate beginner's guide to data modeling, visualization, digital storytelling, and more (Third edition, colored version.). Packt Publishing Ltd.

Other material listed in the learning environment (Moodle).

Teaching methods

Contact lessons at Rajakatu Campus
Independent exercises
Quizzes
Pair work

Employer connections

Possible company visitors will be confirmed during the course.
Learning assignment can be done as a commission to a case company.

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 20h
Independent familiarization with learning material 24h
Exercises and assignments 37h

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.
This course is targeted also to students in Tourism management and Service Business (2.-3. year, elective studies).

The assessment of the course is based on the following credits:
exercises and assignments (100%, 3 ECTS)