This research focuses on Big Data Facilitators, companies that can help to reduce the complexities of Big Data and offer the value residing in it. These types of companies are highly unexplored, thus the purpose of this research paper is to create an understanding of Big Data Facilitators by studying their drivers and barriers concerning Big Data application, and their general role in the business ecosystem. To answer the overarching purpose four research questions has been proposed: RQ1: What drivers are prominent for Big Data Facilitators concerning the application of Big Data Analytics? RQ2: What barriers are prominent for Big Data Facilitators regarding the application of Big Data? RQ3: What value do Big Data Facilitators offer for their customers? RQ4: What type of customer do Big Data Facilitators offer value to? To answer these questions two phases of research were conducted. Phase one consisted of interviews with 10 different Big Data Facilitators, with the primary focus of understanding their drivers and barriers. The second phase consisted of qualitative analysis of text on websites from 27 Big Data Facilitators, with the primary focus of understanding what value these companies offer and what general customer type they target. The study found that the primary drivers for these companies are Technology as an Enabler, Organisational Knowledge, Agile Organisational Structure and Innovative Foundation and the barriers are Finding Correct Expertise, Process Difficulties, Resource Restrictions and Security Issues. This resulted in the adapted force-field model which shows a weighted representation of these factors. The identified generalizable value being offered was found to be Improved Processes, Innovative Technology, Insight and Convenience. A model called the Four-dimensions model was created with the two phases as basis. It represents an aggregation of the primary factors of influence affecting Big Data Facilitators as well as the value that they offer and most importantly, how the parts interrelate. This thesis provides further depth to the research around Big Data and Big Data analytics, as well as insight in the highly unexplored topic of SMEs relationship with Big Data and Big Data analytics. This since the Big Data Facilitators at hand were either start–ups or small enterprises. Moreover, the research added insight into the almost non-existent research area of Big Data Facilitators and analytics vendors. The managerial implications suggest that companies should strive to, first create an environment for innovation to prosper and continuously strive for keeping an agile organisation structure, by ensuring flexibility, adaptive processes and short lines for data-driven decision making. Second, to create awareness and utilization of the tools and open source–software available during its rapid development. Third, create an attractive environment for managing organisation knowledge and attracting the right expertise needed to understand the complexities of Big Data and handle the abstract algorithms in machine learning and deep learning
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-69589 |
| Date | January 2018 |
| Creators | Johansson, Johan |
| Publisher | Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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