2014
DOI: 10.1007/s00287-014-0806-4
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Big Data, Big Opportunities

Abstract: Edited by Brian HamblingThis best-selling software testing title explains the basic steps of software testing and how to perform effective tests. It is the only official textbook of the ISTQB-BCS Certified Tester Foundation Level, with self-assessment exercises, guidance notes on the syllabus topics and sample examination questions. 'This book covers all the sections of the latest 2018 CTFL syllabus and more. It is not just written as an exam aid though, it is a reference for software testing in its own right.… Show more

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Cited by 9 publications
(3 citation statements)
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“…Occasionally, authors define the term data scientist instead, as in [9,38].A strong, widely accepted definition of the term data science would certainly form a foundation for coherent, well-grounded data science teaching, but lecturers need to make decisions on the teaching content in courses offered now. In the current fast paced times, there is little alternative: businesses and society are demanding data scientists now [9,38,58,65,66]. Waiting for the long-lasting, comprehensive discussion on a definition for data science to be settled is not an option.…”
Section: The Need For a Clear Definitionmentioning
confidence: 99%
“…Occasionally, authors define the term data scientist instead, as in [9,38].A strong, widely accepted definition of the term data science would certainly form a foundation for coherent, well-grounded data science teaching, but lecturers need to make decisions on the teaching content in courses offered now. In the current fast paced times, there is little alternative: businesses and society are demanding data scientists now [9,38,58,65,66]. Waiting for the long-lasting, comprehensive discussion on a definition for data science to be settled is not an option.…”
Section: The Need For a Clear Definitionmentioning
confidence: 99%
“…"Knowledge is Power" diese Aussage ist in der heutigen Zeit sehr treffend (Mayer-Schönberger und Cukier 2013). Der Gesellschaft und somit auch den Unternehmen stehen immer mehr Daten zur Verfügung (Wrobel, Voss et al 2015). Das durchschnittliche Unternehmen hatte bereits 2014 circa 427-mal so viele Daten wie jemals in der US Kongressbibliothek gespeichert wurde (Davenport und Paulus 2014).…”
Section: Ausgangslage Und Problemstellungunclassified
“…Die gängigsten Definitionen beinhalten jedoch die sogenannten vier V's: Volume, Velocity, Variety und Veracity. Dabei sind die am häufigsten in der Literatur genannten Eigenschaften von Big Data Volume, Variety und Velocity (Bendler et al 2018;Dijcks 2013;Dorschel 2015;Gluchowski und Chamoni 2016;IBM 2017;Inmon und Linstedt 2015;Mayer-Schönberger und Cukier 2013;Wrobel et al 2015). Die Eigenschaft "Veracity" wurde aufgrund der stetig wachsenden Social-Media-Daten erst später hinzugefügt.…”
Section: Ausgangslage Und Problemstellungunclassified