Essentials of Business Analytics

Business Analytics combines data science with business, economics, and management. It focuses on collecting, processing, and analyzing data to develop models that support decision-making. This course covers key methods such as regression, classification, and clustering.

Knowledge

The student will acquire knowledge about:

• Drivers and trends shaping the field of business analytics
• The business analytics life cycle
• How business analytics supports key business functions
• Core concepts and principles of business analytics
• Methods for data collection and an overview of common data sources
• Foundations of data visualization
• Basic statistical and regression methods
• Fundamental concepts of optimization
• Basic methods for classification and clustering
• Introductory concepts of artificial neural networks

Skills

The student will be able to:

• Retrieve data from a variety of open and proprietary sources and import it into Excel spreadsheets or Pandas data frames
• Visualize data using tables, plots, and diagrams in Python
• Apply basic programming skills in Python
• Conduct statistical analyses using Python
• Implement optimization and simulation models in Python
• Discuss and critically reflect on the value and limitations of analytical tools for business decision-making

General competence

The student gains an understanding of how business analytics can be applied to address business challenges and support decision-making. The student becomes familiar with the processes involved in collecting, analyzing, and reporting business data, and develops the competence to use appropriate software tools to carry out business analytics tasks.

Lectures (physical or digital), videos, written exercises, data exercises and essay writing.