Data Analysis and Strategy (SZF_164)
About Study Course
Objective
Learn and understand quantitative and qualitative analysis options for strategic elements of the organization (value chain, business capabilities, business processes, goals and organizational structure) using data analysis and business intelligence (BI) techniques.
Prerequisites
Prior knowledge of data analysis fundamentals, data sources, data structures, and visualization is required. Prior knowledge of organization management principles is desirable.
Learning outcomes
1.At the end of the study course, the students have gained in-depth knowledge about the possibilities of explaining the organization's activity with the help of data analysis and the value that such analysis can provide; - able to apply data analysis techniques and approaches appropriate to the business task; - have acquired practical skills in creating a data analysis task, loading data from various data sources, data modelling and data visualization; - able to formulate and define examples of the application of data analysis, machine learning and artificial intelligence; have learned the principles of building the business and technical architecture of data solutions and can name and describe its elements; - familiarized with the approaches to creating a data strategy and its elements.
1.At the end of the study course, students: - can identify and define analytical tasks at the individual and organizational level; - able to create a solution design for analytical tasks; - able to perform data modeling and data visualization according to the business task; - able to choose and apply modern quantitative data analysis methods; - able to assess and explain the business value of data analysis, dashboards and reports; - able to use data analysis to define business models.
1.At the end of the study course, the students will: - be able to independently evaluate and create a data analysis application or solution design according to the business problem; - will be able to choose appropriate tools and analysis techniques for data analysis tasks; - will be able to assess the maturity of the organization in the field of data analysis, record the current situation, develop recommendations for improvements; - will be able to determine the compliance of the organization's analytics with business goals and the degree of automation.
Study course planning
| Study programme | Study semester | Program level | Study course category | Lecturers | Schedule |
|---|---|---|---|---|---|
| Digital Strategy and Artificial Intelligence Management | 1 | Master's | Required | Aldis Ērglis | |
| Digital Strategy and Artificial Intelligence Management | 1 | Master's | Required | Aldis Ērglis |
