Business Analytics (5cr)

Evaluation scale

H-5

Schedule

The course has weekly lessons according to the timetable. A detailed weekly timetable will be made available on the Moodle learning environment if the Director of Studies decides to starts this implementation. The timetable for the returnable learning assignments will follow the lecture timetable.

Implementation methods, demonstration and Work&Study

Depending on the implementation, learning takes place in contact lessons, independent studies, teamwork and online studies. The course includes the assessment of one’s own learning.

The course has a project work, which is centered around a business case to which several data analytics project management as well as descriptive and predictive data analytics methods are applied. The topic may represent a real case in a company, or it may be picked up from a set provided by the course organiser. In the case study, the student will learn both how to create value for business as well as how to apply business analytics methods. This casework is done in student teams.

In addition to the project work, the following learning methods are used: flipped classroom method, in-class and individual assignments, teamwork in contact lessons, and online lessons.

Recognition of prior learning (RPL)

If students have acquired the required competence in previous work tasks, recreational activities or on another course, they can show their competence via a demonstration. The demonstration must be agreed with the course teacher. More information and instructions for recognising and validating prior learning (RPL) are available at https://www.haaga-helia.fi/en/recognition-learning Look at "Instructions to students (master)"

Intro

Due to digitalisation, organizations possess more and more data. This data can be leveraged to provide valuable insights for businesses. Data analytics may be used in decision making, marketing, and product development – just to name some very common business cases. This course provides the student with the skill set required to manage business analytics projects and to carry out data analytics tasks in a business context.

Materials

The learning material is mainly distributed through the Moodle learning environment. The course brings together many analytical concepts related to the applications of business. It also provides tools for applied analytics research and thesis work. Such issues are constantly evolving and the course will make use of material produced by the course teachers and otherwise up-to-date material.

Recommended literature: Business Intelligence, Analytics, Data Science, and AI. A Managerial Perspective. Sharda, Ramesh, Delen, Dursun, Turban, Efraim.Pearson Education Limited 2024.

Teaching methods and instruction

This course implementation has lessons every week. The lessons include relevant analytical principles and the use of considered technical tool in calculations. Some of the lessons are intended to the guidance of course assignments. In particular, for each course assignment before the submission date there is an associated lecture.

The course implementation welcomes independent study of topics, e.g. by means of examples in the course material, within the framework of the Haaga-Helia University of Applied Sciences' guidelines.

No previous experience in coding is required.

Working life connections

The course implementations are designed for students who are about to enter work life or are already working there. The course content takes into account the content used in the field.

Exam dates and re-exam possibilities

The exam will be held at the end of the course on a date to be mutually agreed upon participants during the course. The date of the re-examination will also be agreed together during the implementation.



In all exams and retakes participant must be present in Pasila, where the identity of the examiner will be verified.



In the case of examinations, the participant has extensive access to materials and to the Internet. It is therefore not possible to conduct the test as an Exam test.

Internationality

Mathematical and methodological skills are international skills.

Completion alternatives

There are no shortcuts to learning, and doing the work is essential. Other ways to get your grade in the Haaga-Helia University of Applied Sciences' register of credits should be inquired from the teacher responsible for the course.

Learning assignments

The topics presented in the course lectures are learned by doing related exercises. Assignments will be returned regularly throughout the course. Assignments will be given and returned via Moodle.

The learning tasks will practice the use of applications of analytical concepts and their applications.

Assignments will be among the following topics: business analytics concepts and tools, descriptive analytics and business intelligence, enterprise modeling for analytics, introduction to machine learning, predictive analytics and prescriptive analytics, knowledge-based methods

Assessment methods

The learning assignments account for 100% of the final grade.