Data Engineering and Analytics (MSc)

["The creation and storage of large data sets becomes feasible and economically viable, for example, due to price decreases in storage space, sensors, smart devices, social networks, and other factors.", "Technical advances, for example, in multi-core systems and cloud computing, make it possible to examine data sets on a large scale.", "Such amounts of data not only have their origin in the "classical" domains like business data, but are now created in many areas of life. Consider vehicles that create sensor data and share information via intelligent networking, or consider data that is created by intelligent energy grids.", "Data Analysis is concerned with the fundamentals of understanding and modelling data and the underlying relationships therein. It is also concerned with topics that require solid mathematical foundations, including the following: Fundamentals of Convex Optimisation, Computational Statistics, and more.", "Data Engineering consists of lectures about the construction of systems that perform efficient and scalable data processing, thus enabling methods of data analysis on large data sets. This area of study also contains lectures about distributed systems, distributed databases, query optimisation, database systems on modern CPU architectures, and high performance computing. The curriculum comprises mandatory courses on Data Analysis and Data Engineering.", "Data Engineering and Analytics offers lectures about machine learning, business analytics, computer vision, and scientific visualisation."]