The course focuses on how companies leverage information technology and data analysis to facilitate value creation by bridging the technological and business-related theoretical domains. The aim of the course is to prepare participants for having a critical thinking in the context of companies, start-ups, and organizations that are adopting data-driven and information-system-based approaches to bring value to different stakeholders. The advent of data availability at large, advanced analysis techniques, and technologies create opportunities for all stakeholders, but also raise challenges. The course involves forming an analytical understanding of how data availability, systems, and analysis techniques can be implemented through appropriate operations and strategies to overcome the challenges and to create value. This course builds upon the foundation of “Introductory Business Intelligence” and expands the technical foundation with specific managerial considerations and more advanced implementations of learned approaches.
This course intends to introduce different topics and problems that are subject of business intelligence, data analysis, and machine learning. The course introduces knowhow of gathering and preparing data, visualizing data, applying simple sentiment analysis, utilizing database technologies, and basic machine learning and prediction modelling. This introductory course gives further knowledge of business intelligence through Python. Through hands-on exercises and projects, it provides approaches and practices to enhance the skills of solving problems in business intelligence.
The aim of the course is to provide students with an overview of important tasks related to projects in a business context. We will focus on defining projects, human aspects of projects management and IT tools (scheduling software, project extranets) used to support management, control and follow up projects as well as knowledge exchange. During the course the students will develop their skills of working as project managers.
The course can be taken by students from both Helsinki and Vaasa.
- Teacher: Patrik Paetau
This course provides an introduction to how data sources on the web can be utilized to gain insights relevant to decision-making in business and society. This covers learning the main steps and considerations that relate to acquisition, cleaning and formatting of data in preparation for analysis, and learning approaches to data visualization and reporting. The course combines practical data work with supporting readings from data science literature, facilitating introductory reflection over data-driven insight and decision-making. The course is built around use of Tableau for which support is exclusively provided, but deliverables building on data can also be completed by use of any other suitable software and syntax you may want to use (e.g. R, Python).
This course is one of the two courses in the Global competence module, mandatory for all master's degree students at Hanken who have started their master's studies 1.8.2018 or after.
- Teacher: Mikael Laakso
The aim of the course is to give fundamental insights and skills in programming applications and data analysis using the Python syntax. Python is a pivotal tool for performing the tasks in data analysis, business intelligence, machine learning, etc. The course, thus, provides a solid starting point to continue learning more advanced topics in business intelligence. During the course you will be writing your own business-related projects, resulting also in a better understanding of existing projects. Through the exercises you are trained to use modern programming approach for business-related problem solving.