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020 _ _ |a 978-3-031-08411-9
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100 1 _ |0 P:(DE-2719)2810759
|a Meigen, Christof
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245 _ _ |a Data and Knowledge Management
250 _ _ |a 1st ed. 2022
260 _ _ |a Cham
|b Springer International Publishing
|c 2022
295 1 0 |a [Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022,
300 _ _ |a 101-119
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490 0 _ |a Studies in Big Data
|v 112
520 _ _ |a 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.
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650 _ 0 |a Engineering—Data processing
650 _ 0 |a Bioinformatics
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700 1 _ |a Apke, Alexander
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