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ZENODO
Report . 2017
License: CC BY NC SA
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Report . 2017
License: CC BY NC SA
Data sources: Datacite
https://dx.doi.org/10.24406/pu...
Other literature type . 2017
Data sources: Datacite
https://zenodo.org/record/8030...
Other literature type
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Big-Data-Analytik: Datenbasierte Optimierung produzierender Unternehmen

descriptionPublicationkeyboard_double_arrow_right Other literature type , Report 01 Jan 2017Publisher:Fraunhofer-Gesellschaft
Authors: Bauer, Dennis; Maurer, Tobias; Henkel, Christian; Bildstein, Andreas;

doi: 10.24406/publica-r-298545 , 10.5281/zenodo.803099 , 10.5281/zenodo.803098

Big-Data-Analytik: Datenbasierte Optimierung produzierender Unternehmen

Abstract

Big Data Analytics aim at a meaningful use of data to generate benefits for organisations. Nevertheless, manufacturing small and medium-sized enterprises (SME) do not tend to use these technologies nowadays. With the survey "Big Data Analytics: Data-driven optimization of manufacturing companies" (German title: Big-Data-Analytik: Datenbasierte Optimierung produzierender Unternehmen) Fraunhofer IPA shows the “potential” transformation of manufacturing companies when using big data technologies. Based on the analysis of the survey data, development areas and offers of support for SMEs have been derived.

Related Organizations
Keywords

Big Data, SME, Manufacturing Companies, Transformation

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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