Explore our knowledge

MSc in Business Administration and Data Science

Busi­ness Data Pro­cessing and Busi­ness In­tel­li­gence

About the course

Subjects
IT

Course content

Data-driven decision making is a core component of modern business practice. As a result, it is increasingly important for business students to understand the end-to-end process of business data analytics.
This course provides foundational knowledge of the major stages of business data analytics, including data collection, storage, processing, and reporting. Students gain hands-on experience with real datasets and learn the complete analysis lifecycle through practical examples. Topics include:

 

  • Introduction to Data Collection via Web APIs: How data is retrieved from APIs and open web services, and the role of API frameworks in digital echo systems. 
  • Data Formats: Overview of common data formats used for digital data exchange.
  • High level understanding Data Storage models for operational as well as analytical databases 
  • Data Storage Models: High-level understanding of storage approaches for operational and analytical systems.
  • Relational Databases: Structure and functions of relational database management systems.
  • NoSQL Databases: Brief introduction and comparison with relational databases.
    Structured Query Language (SQL): Using SQL for querying, aggregating, and filtering data. Using SQL as a quick reporting tool.
  • Data Warehouse Concepts: Introduction to data warehouse architectures and schema designs.

Tools: Tableau or Power BI for reporting; PostgreSQL for relational databases and SQL; MongoDB for NoSQL; and a scripting language or visual tool for interacting with Web APIs interfaces.

See course description in course catalogue

What you will learn

To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors:

  • Demonstrate an understanding of how Web APIs operate and how data can be accessed, stored, and shared through them.
  • Identify and compare standard data formats used to support data exchange in business intelligence processes.
  • Evaluate different data storage and modeling approaches used for managing business data.
  • Demonstrate understanding of relational database structures and apply SQL to process, manage, and retrieve business data.
  • Describe an understanding of complete end to end business data analysis process
  • Demonstrate application of analytical skills to implement data processing tasks and develop insights with Business Intelligence and reporting tools.
  • Show competence in applying data analysis and reporting tools to prepare, explore, and present business data.

Course prerequisites

The are no pre-requisites however student should be able to install software and setup configurations following step by step guidelines

Facts

Level
Master
Type
Elective
ECTS
7.5
Code
CD­SCV1005U
Teaching periods
Autumn – semester
Academic year
2026/2027
Status
Available places
Teaching language
English
Teaching Format
Hybrid
Exams
  • Written exam on campus
    Individual exam, winter
Assessment type
  • 7 point grading scale