Cloud-based big data analytics for improving the processing of customer’s data in SME’s

This research would integrate cloud-computing technology with big data analytics for creating value and improving the analytics based on customer’s data. The aim is to improve the data processing to get better insights into the customer’s data and effectively analyse the patterns of the customers in order to fulfil the requirements of the customers for the revenue growth of the company. The objective of this research is to improve data processing using big data analytics. The three-factor taxonomy would be proposed comprised of three major components DSA (Data acquisition, Storage, and Analytics) for the management of customer’s data. The purpose is to get big insights into the customer’s data and analyse the customer’s patterns effectively by integrating cloud technology and big data analytics for the design innovation in SMEs. The expected outcome of this study will be the improved the data processing and processing of customer’s information for the design innovation in SMEs. The study contributes to the integrity, security, consistency, and amplifying the scalability of the data. The 12 research papers will be analysed in order to assess existing research and demonstrate the efficacy of DSA taxonomy. Some components of the taxonomy would be validated and even fewer would be evaluated in this study for improving the customer’s data processing in SMEs.