Evaluation model for the analysis of data maturity

被引：0
|
作者：
Eickelmann M. [1 ]
Wiegand M. [2 ]
Deuse J. [3 ]
Bernerstätter R. [4 ]
机构：
[1] Ruhr Universität Bochum, Germany
[2] Technischen Universität Dortmund, Germany
[3] RWTH Aachen, Germany
[4] Universität Leoben, Austria
来源：
ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb | 2019年 / 114卷 / 1-2期
关键词：
Machine learning - Metadata;
D O I：
10.3139/104.112037
中图分类号：
学科分类号：
摘要：
Determination of the data maturity level for the application of machine learning methods in industrial manufacture. The digital transformation of business processes leads to a steady increase in available data. For the efficiently use of knowledge hidden in the data, companies are striving for the application of machine learning methods. Data quality is of outstanding importance for the applicability of machine learning methods and the quality of the results. This paper presents a model for the derivation of data maturity, to evaluate the chances of success of industrial data analytics projects and identify necessary steps for the improvement of data maturity. © Carl Hanser Verlag GmbH & Co. KG.
引用
收藏
页码：29 / 33
页数：4
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