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 core of business processes in the current age. It has become ever more important for business students to get acquainted with end to end process for business data analytics. 

 

The aim of this course to provide knowledge about all processes of business data analytics that includes data collection, data storage, data processing and reporting. Student get hands on experience with data analysis process and learn the complete life cycle of analysis with examples and real data sets. Following topics are covered:

 

  • Introduction to data collection using WEB API : Learning how data can be retrieved from APIs and open WEB Api services. Understanding Web API framework is essential to understand data integrations. 
  • Introduction to data formats : Getting familiar with data formats used for data sharing on digital platforms
  • High level understanding Data Storage models for operational as well as analytical databases 
  • Introduction to relational databases and the structure and functions of Relation Database Management Systems
  • Brief Introduction to NoSql Databases : Comparison with Relational Databases
  • Structured Query Language (SQL) : How to use SQL for fetching, aggregating and filtering data.
  • Introduction to Dataware house concepts and schemas.
  • Tools: Tableau or Power BI for reporting, Open source PostgreSQL for Relation Databases and SQL, MONGO DB for NoSql, Scripting language or visual tool for WEB API  
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 data fetch from online data sharing platforms using WEB apis.
  • Compare the standard data formats for data sharing across software platforms
  • Reflect on different data storage and modelling possibilities available for business data
  • Explain and demonstrate knowledge of data processing, data storage and data retrieval using relational database structure and structured query language
  • Demonstrate high level understanding for NoSQL databases
  • Describe an understanding of complete end to end business data analysis process
  • Apply analytical skills for implementation of business data processing using Business Intelligence and Reporting tools
  • Substantiate expertise for using data analysis and reporing tool

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
2025/2026
Status
Available places
Teaching language
English
Teaching Format
Hybrid
Exams
  • Written assignment
    Individual exam, winter
Assessment type
  • 7 point grading scale