Course - Essentials of Business Analytics - BBAN3001
Essentials of Business Analytics
About
About the course
Course content
Business Analytics is an interdisciplinary field that combines data science with business, economics and management. Business analytics deals with the collection, processing and analysis of data as well as the development of explanatory, predictive and normative models to support decisions and solve problems.
Learning outcome
Knowledge
The student will acquire knowledge about:
- the drivers and trends of business analytics,
- the business analytics life cycle,
- how business analytics is useful in central business functions,
- central concepts of business analytics,
- data collection and data sources,
- data visualization,
- basic statistical and regression methods,
- basic concepts of optimization,
- basic methods for classification and clustering,
- basic concepts of artificial neural networks.
Skills
- The student can retrieve data from different open and proprietary data sources and import these data into Excel spreadsheets or Pandas data frames.
- The student knows how to visualize data with tables, plots and diagrams in Python.
- The student acquires basic programming skills in Python.
- The student can carry out statistical analyses by means of Python.
- The student can implement optimization and simulation models in Python
- The student can discuss and reflect on the usefulness of analytics tools for business decisions.
General competence
The student gains expertise in how business analytics can be used to address and solve business problems and decision making. The student becomes familiar with the processes involved in collecting, analyzing and reporting business data. The student acquires skills to handle business analytics with appropriate software.
Learning methods and activities
Lectures (physical or digital), videos, written exercises, data exercises and essay writing.
Compulsory assignments
- Mandatory Essay
Further on evaluation
In the exam, the majority of exercises need to be implemented by means of Python.
In the case of a re-sit exam and the last exam after the course has been discontinued, the form of assessment may be changed to an oral exam.
Required previous knowledge
Elementary course in mathematics and statistics.
Course materials
The curriculum will be announced when the course commences.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| TDT4172 | 3.5 sp | Autumn 2025 |
Subject areas
- Economics and Administration
Contact information
Course coordinator
Department with academic responsibility
Examination
Examination
Ordinary examination - Autumn 2025
School exam
The specified room can be changed and the final location will be ready no later than 3 days before the exam. You can find your room location on Studentweb.