Data and Information Analyst 2
Department of Applied Computer Sciences

Data and Information Science

The course will start in Autumn 2018 subject to approval.

 
  • Academic Degree:

    Master of Science in Engineering (MSc)

  • Mode of Study:

    Work-friendly / 4 Semester / 120 ECTS

  • Language of Instruction:

    German

  • Head of Degree Programme:

    MMMMag. DDr. Wolfgang Granigg (interimistisch)

  • Campus:

    Graz

  • Application Deadline:
    20 March 2018 more deadlines

We provide you with a first-class all-round education in the field of data and information analysis, including design, organisation, storage, analysis, visualisation and communication of large data sets. Data and information are used to generate valuable analyses such as prediction models. The course provides all the essential methods and tools you will need.

Data and Information Analyst 20

Did you know, …

… that a wide range of careers are open to our graduates?

Potential employers include companies in the banking and insurance industry, e-commerce and online marketing, pharmaceuticals, bioinformatics and healthcare through to companies involved in business management applications of data mining, such as business & predictive analytics in digital production.

Data and Information Analyst 10

Did you know, …

… that the course is organised in a work-friendly manner?

Lectures are held from Wednesday to Friday in the first year, only one day a week in the 3rd semester, and in a block of five weeks at the start of the 4th semester. In this way you can combine your studies, especially the projects and the Master's thesis, with part-time employment. Weekends are free. E-learning accounts for a small portion of classes.

Data and Information Analyst 3

Did you know, …

… that there is great demand for experts in data and information analysis?

Most companies have a huge amount of electronically stored information. Even if data warehouses have been established, the stored information is often not used professionally, e.g. using methods of data condensation, processing and development. These companies need experienced professionals who use their data to generate information and knowledge for decision-making documents, regular analyses or for process control.