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Technology selection for big data and analytical applications


  • Lehmann, Denis
  • Fekete, David
  • Vossen, Gottfried


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.

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  • Lehmann, Denis & Fekete, David & Vossen, Gottfried, 2016. "Technology selection for big data and analytical applications," ERCIS Working Papers 27, University of Münster, European Research Center for Information Systems (ERCIS).
  • Handle: RePEc:zbw:ercisw:27

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    Big Data; Analytics; Technology Selection; Architecture; Reference Architecture; Selection Framework;

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