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What makes big data different from a data quality assessment perspective? Practical challenges for data and information quality research

: Kläs, Michael; Trendowicz, Adam; Jedlitschka, Andreas

Volltext urn:nbn:de:0011-n-3994925 (308 KByte PDF)
MD5 Fingerprint: f2633ada08f1766b42a00f52c6c04f7c
Erstellt am: 24.6.2016

Kaiserslautern, 2015, 5 S.
IESE-Report, 071.15/E
Reportnr.: 071.15/E
Bericht, Elektronische Publikation
Fraunhofer IESE ()
Big Data; data quality; quality assessment; challenge

High-quality data is a prerequisite for most types of analysis. However, since data quality does not come for free, it has to be assessed and managed continuously. The increasing quantity, diversity, and velocity that characterize big data today make these tasks even more challenging. We identified challenges that are specific for big data quality assessments and provide some pointers to promising solution ideas. Moreover, we motivate why big-data-specific challenges may also be worth to be considered when the quality of open data is in focus.