Big Data – Towards Data-driven Business
Ylijoki, Ossi (2019-04-12)
Väitöskirja
12.04.2019
Lappeenranta-Lahti University of Technology LUT
Acta Universitatis Lappeenrantaensis
School of Engineering Science
School of Energy Systems, Energiatekniikka
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Julkaisun pysyvä osoite on
http://urn.fi/URN:ISBN:978-952-335-347-3
http://urn.fi/URN:ISBN:978-952-335-347-3
Tiivistelmä
This research stems from the disruptive phenomenon known as digital transformation, i.e. the pervasive use of digital technologies in order to add value in business. As a side effect of digital transformation, vast amounts of various types of data are generated at a fast pace. This data is known as big data. The data is the root source of added value that businesses look for. Big data represents first and foremost a major paradigm shift, a new way to view businesses, enabled by related technology. However, the paradigm shift towards data-oriented business models and processes is challenging to incumbent enterprises. The aim of this research is to help incumbents to move towards datadriven business models and processes.
This dissertation is based on articles published in scientific journals. The articles are presented in the Publications section of this dissertation. Each of the articles applied different research methods, which is justified by the fact that big data is an emerging concept. The approaches included a literature review, a survey and a case study, as well as algorithmic approaches. Together the articles explore the big data landscape from several angles, both from the theoretical and practical viewpoints.
The results can be viewed as a high-level framework that addresses the primary research question – understanding and utilising big data in the transformation process towards big data driven business – by explaining the phenomenon as well as the value creation processes and connecting theoretical aspects to practice. The theoretical foundations of this dissertation combine strategic management, data-driven innovations and big data in a way that helps to understand the digital transformation process.
This dissertation explains, how big data value creation mechanisms work. It helps to understand the nature of the big data phenomenon and provides building blocks and guidance for practitioners. The results suggest that big data must be seen as a business initiative instead of technological matter and strengthen the perception that big data in general and data-driven innovation in particular are potential sources of added value.
This dissertation is based on articles published in scientific journals. The articles are presented in the Publications section of this dissertation. Each of the articles applied different research methods, which is justified by the fact that big data is an emerging concept. The approaches included a literature review, a survey and a case study, as well as algorithmic approaches. Together the articles explore the big data landscape from several angles, both from the theoretical and practical viewpoints.
The results can be viewed as a high-level framework that addresses the primary research question – understanding and utilising big data in the transformation process towards big data driven business – by explaining the phenomenon as well as the value creation processes and connecting theoretical aspects to practice. The theoretical foundations of this dissertation combine strategic management, data-driven innovations and big data in a way that helps to understand the digital transformation process.
This dissertation explains, how big data value creation mechanisms work. It helps to understand the nature of the big data phenomenon and provides building blocks and guidance for practitioners. The results suggest that big data must be seen as a business initiative instead of technological matter and strengthen the perception that big data in general and data-driven innovation in particular are potential sources of added value.
Kokoelmat
- Väitöskirjat [769]