Title :
Increasing the Value of Big Data Projects -- Investigation of Industrial Success Stories
Author :
Tiefenbacher, Katja ; Olbrich, Sebastian
Author_Institution :
Univ. of Duisburg-Essen, Duisburg, Germany
Abstract :
This paper investigates the constituents of Big Data and their contribution to its success. The starting point is the mainstream understanding of Big Data, which defines the volume, variety and velocity (3V) of the underlying data as main properties of the Big Data phenomenon. This definition is challenged through the presented analysis of more than 100 success stories which are offered by vendors of Big Data technology and solutions. By applying elements of the grounded theory method, the paper goes beyond an overview. The property of variety (which seems to be of particular interest) and structures of the outcome of Big Data projects are discussed. A major implication is that there is a crucial difference between Big Data use cases incorporating all 3Vs and those incorporating less. When all three properties are involved, a new phenomenon arises from embracing new data sources that are within and beyond the organizational borders.
Keywords :
Big Data; 3V; Big Data projects; Big Data use cases; data sources; grounded theory method; industrial success stories; volume-variety-and-velocity; Big data; Data models; Encoding; Market research; Media; Organizations;
Conference_Titel :
System Sciences (HICSS), 2015 48th Hawaii International Conference on
Conference_Location :
Kauai, HI
DOI :
10.1109/HICSS.2015.43