WS24/25

“Data integration is the 800-pound gorilla in the corner, and everyone’s got it in spades,” according to Mike Stonebraker, MIT professor and Turing Award Laureate. The most challenging and time-consuming task of data scientists in the era of Big Data is to consolidate data from different sources, overcoming dirty data, heterogeneity in data representations, and incompleteness of data. In this course, we will surface the entire pipeline of an information integration workflow, by learning about existing integration architectures, algorithms in data cleansing, schema matching, and data fusion. Furthermore, we will discuss state-of-the-art systems and prominent use cases of information integration techniques.