Data Management and Analytics Specialisation (DAMA)
In the interdisciplinary context of Data Science and Big Data, the Data Management and Analytics (DAMA) specialisation covers scalable and distributed data management systems, information retrieval and data mining algorithms, as well as information visualisation and human-data interaction techniques. You will study algorithms, techniques, architectures and methods for the management, processing and interaction with both structured and unstructured data. The acquired theoretical knowledge will be applied in the design of applications that extract insights from streams as data such as for instance produced by Internet of Things devices. There is a detailed list of courses forming part of the DAMA specialisation and an up-to-date list of research topics for MA theses offered by the WISE lab.
The Data Management and Analytics specialisation within the 2-year MsC in Computer Science covers the interdisciplinary aspects of interactive data science and big data management, including scalable and distributed data management systems, information retrieval and data mining algorithms as well as information visualisation and human-data interaction techniques. Our goal is to prepare students for the future challenges in managing and analysing the rapidly growing amounts of data that is produced manually by humans as well as automatically generated by, for example, sensors in emerging Internet of Things solutions, data capturing on the Web or as an outcome of scientific experiments. Thereby, we focus on the scientific aspects and concepts for scalable data management solutions, information retrieval and data mining as well as different information visualisation and interaction techniques rather than on existing mainstream technologies, and provide students the necessary education for a future career as data scientists and data engineers.
As a student in the Data Management and Analytics specialisation, you will study, design and develop big data solutions for the storage, processing, analysis and interaction with big and complex data. Thereby, a special focus is on the system aspects of solutions for big data management and analytics. You will study specialised systems and algorithms for the development of data-intensive applications at scale that store their data in a distributed manner as, for example, used by players such as Google or Facebook as well as needed for future applications in the emerging field of the Internet of Things. You will further learn machine learning and information retrieval techniques to search for information in large collections of documents (e.g. as applied in Google's search algorithms) and study the theory as well as practical aspects for the automatic detection of structure in big and complex data. This knowledge about methods and techniques for the machine-based analytics of large datasets will play a major role in future business solutions since it is not enough to capture the data without having the tools and skills to further process, analyse and get new insights from these datasets. Given that many analytical tasks cannot automated, you will also learn about state-of-the art information visualisation and interaction techniques which keep the human in the loop, augment the human capabilities and enable the exploratory analysis of big and complex datasets. You will further learn how to design interactive visualisation solutions for the presentation of known data-supported facts to support decision making processes as well as the delivery of existing knowledge.
