Introduction to Data Analytics for Business (5 cr)
Code: ANA001TR1AE-3030
Basic information of implementation
- Enrollment
- 02.06.2025 - 17.10.2025
- Enrollment for the implementation has begun.
- Timing
- 20.10.2025 - 12.12.2025
- The implementation has not yet started.
- ECTS Credits
- 5 cr
- Campus
- Pasila Campus
- Porvoo Campus
- Teaching languages
- English
- Seats
- 30 - 100
- Degree programmes
- ITBBA Business Information Technology
- Teachers
- Toni Ernvall
- Groups
-
ITE2PAICB1Business Information Technology, 2nd semester, ICT and Business, Pasila, group 1
-
ABEV3PCAVIAviation Business, 3rd semester, Open Path Admission, Virtual
-
VIRTUALVirtual implementation
-
INSTRUCTEDInstructed virtual implementation
- Course
- ANA001TR1AE
Evaluation scale
H-5
Implementation methods, demonstration and Work&Study
CONTACT
ONLINE
BLENDED
VIRTUAL
If you have acquired the required learning outcomes, you can show your competences with a demonstration. If you have any questions, please contact the responsible teacher. More information and instructions regarding the recognition of learning: https://www.haaga-helia.fi/en/recognition-learning
Intro
The amount of data available today is enormous. For example streaming services collect data from millions of users, companies with loyalty card gather information about consumption habits, etc. The massive amount of data does not provide any benefits unless you know how to summarize, visualise and interpret it. In this course you will familiarise yourself with basic data-analysis methods needed in business - you will learn how to turn data into useful information.
Materials
Material available in Moodle
Recommended reading: Grady Klein and Alan Dabney: The Cartoon Introduction to Statistics
Teaching methods and instruction
Video lectures, self-studying material available in Moodle.
Assignments and exam.
Exam dates and re-exam possibilities
Will be informed in the beginning of the course.
Learning assignments
Exercises on descriptive statistics, correlation, regression, statistical inference etc.
Assessment methods
Exercises and exam.
You must pass the exercises and the exam to pass the course.