TY  - CHAP
AU  - Meigen, Christof
AU  - Dörpinghaus, Jens
AU  - Weil, Vera
AU  - Schaaf, Sebastian
AU  - Apke, Alexander
TI  - Data and Knowledge Management; 1st ed. 2022
VL  - 112
CY  - Cham
PB  - Springer International Publishing
M1  - DZNE-2023-00422
SN  - 978-3-031-08411-9
T2  - Studies in Big Data
SP  - 101-119
PY  - 2022
AB  - Data and Knowledge Management, sometimes also called Information Management, is a core topic of Data Engineering and Data Mining. It is also an interdisciplinary field, touching economics (how efficient and expensive is the solution?), psychology (does one use this solution in a way that was intended?) and, of course, informatics. This chapter offers a theoretical overview on Data and Knowledge Management and thus provides a theoretic foundation for the following parts of this book. Moreover, if you implement or plan a solution in the field of data mining or data engineering, carefully consider the information given here. In other words: Besides the theory, this chapter provides a technical blueprint.
LB  - PUB:(DE-HGF)7
DO  - DOI:10.1007/978-3-031-08411-9_5
UR  - https://pub.dzne.de/record/257353
ER  -