The Business Informatics Master's program has a very broad scope which is both its main strength and weakness. A majority of the offered content overlaps with the Data Science Master's program so if one is interested in that domain, the Data Science program is definitely the right choice as it is more specialized. As for the BI program, one can also enroll for courses in other domains such as economic modelling, simulation, management sciences and enterprise engineering (recommender systems, e-commerce, etc.). However, one must be careful with this broad range of options. I'd say with great choice comes great responsibility. Enrolling for just the core modules of multiple domains feels like just scratching the surface of everything and missing on acquiring specific and deepened knowledge in any given field. As the content is vast, lecturers only manage to teach the foundations, leaving students asking themselves - "What did I actually learn here?". I would strongly recommend evaluating the different modules and sticking to a few concrete ones (taking both the core and extended modules) rather than completing all core modules. Choose a few domains of business informatics you want to know a lot about, rather than know little about all of them.
As for the study content, there is a good balance between interesting and not that interesting material. While not every lecturer has the perfect approach to teaching (in my opinion), there are many lecturers who do a great job of making those boring theoretical lectures sound interesting (Allan Hanbury, Martin Bicher, Ulrike Schneider and Henderik Proper being some of them). As is natural for an university, one cannot expect to graduate and be fully practically prepared to jump in on the job market and find the perfect job as more emphasis is put on theoretical knowledge and academical approach (performing research, writing papers and conducting experiments rather than practical experience with concrete technologies). That is not to say there are no practical exercises. Solo and (predominantly) team assignments are given in almost every course, which are usually very thorough and time consuming but are related to doing experiments and answering research questions. For example, the last assignment I worked on consisted of answering questions on and predicting wildfire severity in Europe using data analytical approaches, where we had to both do the data science part (Python) but also search for suitable datasets, make assumptions and argument and present every step of the process of how and why we answered the research questions. Nevertheless, the program is by no means a software programming/computer engineering program where you develop apps and systems. On the contrary, it has comparatively little to do with programming.
Finally, in terms of equipment and organization, everything is perfect. A clean, well structured and organized western university. If you are coming from Eastern Europe as I did, you definitely will be impressed :).