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Big Data and Cloud Computing are emerging as a new trend in the knowledge industry. Big Data has enabled competitive advantages that many technology firms want to possess. And Cloud Computing has been used to address the significant investment requirements that Big Data requires. Supported by leading organizations in IT industry, Big Data and Cloud Computing adoption have been significant in the recent years. This thesis explores a way that organizations can develop and deliver Big Data application on the Cloud. As a part of the Tekes funded project named SGEM, this is a pilot study to deploy Big Data and Cloud Computing technology in the context that Case Company is developing an asset management service for Target Customer. The service analyzes disturbance records in the electricity distribution network of the Target Customer and combines weather and geographical data to assist maintenance decisions. In this thesis, an overview of Big Data and Cloud Computing technology and possible business models for Cloud Computing will be thoroughly described. The viability of its implementation process will also be analytically examined. In the case study, Big Data and Cloud Computing will be deployed in the industrial context that then lead to a proposal of novel approach to solve Target Customer’s problems. The application is tested against data from one medium-voltage substation between 2011 and 2014 and is verified against field tests between 16 to 19 on April 2012. The collective data in this thesis assure the feasibility of this emerging technology to be implemented in service industry. The case study demonstrates an optimal workflow that can be practically applied in real life situations. Finally, it reveals opportunities for further research in Big Data and Cloud Computing area.N/