Application and Adoption of Big Data Technologies in SMEs

Recent years have witnessed a phenomenal growth in Small and Medium-Sized Enterprises (SMEs) and entrepreneurs all over the world. SMEs have played an essential role in transforming the American economy. SMEs forms 99 percent of all firms in the country, employ more than 50 percent of private sector employees, and account for more than 50% of the country's nonfarm GDP (Brief, 2000). Despite its role in the economy, SMEs are facing challenges in using vast chunks of data available to build a competitive environment that is significant for economic growth (Blackburn, 2016). Much of the data produced can either have a direct or indirect effect on the sector if well processed. Some of the data produced can be used to make relevant policies and decisions regarding supply chain, customer management, and market changes. To make good use of these enormous volumes of data, firms have employed available big data analytics. Although data mining has been in existence for a while now, it is until recently that big data has found its application in business. This paper intends to outline the adoption rates of big data in SMEs in the US. However, concepts of Business Intelligence (BI) was later developed to emphasize the need for the collection, analysis, and interpretation of that data for business use. With the use of BI, much of the produced data have been analyzed to help businesses make data-driven decisions which have helped them understand market trends. SMEs have for a long time used data for recording and monitoring transactions. However, in the recent past, a new awareness of the importance of data analytics have been going around. Consequently, a large number of SMEs have demonstrated an interest in using business analytics.