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Advanced Concepts of Data Analytics and Curation

Business Intelligence, Data Warehousing and Data Mining in Health Care and Research

Hochschule Hannover (HsH) |
University of Applied Sciences and Arts Faculty III | Media, Information & Design

This module is part of the certificateManagement and Analysis of Medical Data

Teaching Language: German, partly English teaching material

Workload: 0h presence / 68h online / 112h self-study = 180h total1 (6 ECTS)

Target Group: Master students in health information management or medical informatics and scientists / executives, that need further training in data integration, curation and analytics in the context of medical research.

Competencies in data analytics and curation have become a key success factor for all research and care processes in medicine.

Pretty young student studying at home sitting at her dining table with a large binder of notes checking something on the screen of her laptop computer
business documents on office table with smart phone and laptop computer and graph financial with social network diagram and three colleagues discussing data in the background
Focused classmates studying together and using laptop in library

Consultation & Registration:
If you have any questions, please do not hesitate to contact us:

Form of teaching: instructional videos, e-tivities, weekly consultation hours, quiz

Learning Objectives

The course introduces concepts and methods of (clinical) data warehouses, data mining and machine learning. The contents of the module are data warehouse conceptual modeling techniques, resulting in multidimensional data models and corresponding data analysis operations as well as the basic principles of data mining respectively machine learning and typical machine learning algorithms. The module is intended to enable the participants to use these methods and technologies in their own scientific work.

The following competencies are taught in detail:

  • Learners know and understand basic concepts and application scenarios of data warehouses and data mining analysis procedures in the context of business intelligence (BI) and knowledge discovery
  • Learners know typical application scenarios of data warehouses in medicine and clinical research and are aware of data quality and curation issues in these fields
  • Learners understand the use and creation of multidimensional data models and the concept of data cubes. They are able to implement Online Analytical Processing (OLAP) methodologies
  • Learners know typical cases of use and the limitations of machine and statistical learning. They can apply these methods and algorithms in typical application scenarios in medicine and clinical research

Embedding:  Being part of the HiGHmed module network, the module of the HsH follows those modules, which relate to data collection topics such as medical image processing and assistive health technologies as well as image and signal-based assistance systems. The HsH module focusses on the integration and consolidation of data from different sources and on useful methods and tools to extract, transform and load the data into a format usable for sophisticated statistical analysis and machine learning methods.

The module concludes with topics on how to proceed with the analyzed data, including the reliable use of data in research and care, patient-centered information management and medical decision support. Hochschule Hannover (HsH) – the University of Applied Sciences and Arts in Hannover focuses on teaching and research, practice orientation, and internationality. With nearly 10.000 students it is the second largest university in Hannover and was established in 1971.


1The times serve as rough orientation. The real times may differ.