Event

This lecture replaces the lecture "Big Data Analytics 2". Our intention is to devote more attention to the Data Science process and to explicitly address the steps of this process. – Data Science techniques are attracting great interest among users, in particular for analyzing large data sets. The spectrum is broad and includes classic industries such as banks and insurance companies, but also newer players, such as Internet companies, social media, natural sciences and engineering. In all cases, the desire is to extract interesting patterns from very large data sets with as little effort as possible, and to monitor the behavior or systems. This lecture deals with the preparation of data as a prerequisite for a fast and efficient analysis as well as with modern techniques for the analysis itself. The course emphasizes phenomena and techniques that were not considered in the lecture "Data Science 1", such as approaches for dealing with data streams, high-dimensional data sets, data integration, and compression and sampling of large data sets.

At the end of this course, participants should have a good understanding of advanced concepts in the field of Data Science und shoud be able to explain them clearly. They should be able to discuss and compare approaches for the analysis and management of large data sets and data streams in terms of their effectiveness and applicability. Participants should understand which problems are currently open in the field of Data Science and have gained insights into the current state of the art.