Arbeitspapier
Technology selection for big data and analytical applications
The term Big Data has become pervasive in recent years as smart phones, televisions, washing machines, refrigerators, smart meters, diverse sensors, eyeglasses and even clothes connect to the Internet. However, their generated data is worthless without information retrieval through data analytics. As Big Data is too big for a single person to investigate, appropriate technologies are being used. Unfortunately, there is not one solution but a large variety of different tools, each of them with other functionalities, properties and characteristics. Especially small and midsized companies have a hard time to keep track as this requires time, skills, money, and specific knowledge which result in high entrance barriers for Big Data utilization. This papers aims to reduce these barriers by explaining and structuring different classes of technologies and basic criteria for proper technology selection. It proposes a framework that guides especially small and mid-sized companies through a suitable selection process that can serve as a basis for further advances.
- Language
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Englisch
- Bibliographic citation
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Series: ERCIS Working Paper ; No. 27
- Classification
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Management
- Subject
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Big Data
Analytics
Technology Selection
Architecture
Reference Architecture
Selection Framework
- Event
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Geistige Schöpfung
- (who)
-
Lehmann, Denis
Fekete, David
Vossen, Gottfried
- Event
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Veröffentlichung
- (who)
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Westfälische Wilhelms-Universität Münster, European Research Center for Information Systems (ERCIS)
- (where)
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Münster
- (when)
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2016
- Handle
- Last update
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10.03.2025, 11:45 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Lehmann, Denis
- Fekete, David
- Vossen, Gottfried
- Westfälische Wilhelms-Universität Münster, European Research Center for Information Systems (ERCIS)
Time of origin
- 2016