Systematic Literature Review Protocol: Adaptations of Data Mining Methodologies

The ‘Big Data’ phenomenon, technological advances in data processing and development of algorithmic techniques have fostered widespread adoption of data analytics across different industries. According to the most recent market studies [1]-[2] adoption rate of ‘Big Data’ analytics tripled for all companies reaching 53% in 2017, up from 17% in 2015. Telecommunications and financial services are the leading industry adopters with 87% and 76% of the respective sector companies already reporting the data analytics usage – well above average figures. They have developed specific datasets, varieties of data and execute broad set of data mining tasks to solve industry-specific business problems. Therefore, both industries are naturally the most suitable sectors for in-depth exploration of data analytics phenomena and its impact on organizations and business practices. Also, both telecoms and financial services explicitly demonstrate the trend of heavy investments into data analytics technologies and competences seeking to realize benefits from data-driven decision-making and maximize ‘Big Data’ business value