@article{HeinzSchildgen, author = {Heinz, Florian and Schildgen, Johannes}, title = {Experience Report: Hey LLM, Generate SQL!}, series = {Datenbank-Spektrum}, volume = {25}, journal = {Datenbank-Spektrum}, number = {2}, publisher = {Springer}, address = {Wiesbaden}, doi = {10.1007/s13222-025-00512-w}, pages = {95 -- 101}, abstract = {Large Language Models have advanced to a resourceful tool with many applications. One particularly interesting use case is the LLM-aided generation of ad-hoc database queries and the possibility of subsequent processing of the results in a way suiting the users intents. In this article, practical ways and experiences are described on how to effectively use LLMs to map a natural-language user query to an SQL query conforming to a specific database schema and post-processing the results of this query in order to, for example, create an appealing visualization. Best results are achieved under favorable circumstances, as, for example, a clean and meaningful named database schema.}, language = {en} } @article{Schildgen, author = {Schildgen, Johannes}, title = {Individuelle Data-Warehousing-Projekte anstelle einer Abschlussklausur}, series = {Datenbank-Spektrum}, journal = {Datenbank-Spektrum}, publisher = {Springer}, issn = {1618-2162}, doi = {10.1007/s13222-025-00502-y}, pages = {4}, abstract = {Dieser Artikel berichtet {\"u}ber die Erfahrungen aus zwei Semestern, in denen Studierende der Data-Warehousing-Vorlesung individuelle Einzelprojekte bearbeitet haben. Das Projekt besteht aus f{\"u}nf Challenges: die Vorstellung der Projektidee, ein Peer-Review anderer Ideen, Datenmodellierung, ETL und analytische Queries, sowie die Erstellung eines Power BI-Dashboards.}, language = {de} }