Big Data for Business Growth in Small and Medium Enterprises (SMEs)
RABIA AHMED BENYAHIA
University ofDjilali Bounaama, Khemis Miliana, Algeria,
E-mail: This email address is being protected from spam bots, you need Javascript enabled to view it
ABSTRACT
Nowadays, big data are considered an extremely valued asset, and its use is foremost important. Small and medium enterprises (SMEs)1 are discovering ways to use this data for their' business growth. This study tries to focus on a literature review of academic research, providing an overview of how SMEs can use big data analytics. It’s found that SMEs need mechanisms, tools, and methods to acquire Data analytics skills than exploit the potential of big data.
5.1 INTRODUCTION
The amount of digital data continues to increase. This proliferation of data is due to the increasing digitization of all areas of the web and the economy. It is in this context that big data was bom; by merging various data sources, structured or unstructured, such as using the Internet on mobility, social networks, geolocation, the cloud, measuring vital data, and media streaming.
The volume of digital data has required thinking of new ways of analyzing, sharing, capture, and storage of data. Thus was bom the “big data.” It is a concept for storing an unspeakable amount of information on a numerical basis.
‘SMEs: Economic literature contains significant differences in the definition of small and medium businesses. Statistical agencies, international organizations, and governments of independent countries emerge with different definitions and categorizations for businesses that do not reflect their differences.
According to the Association for Computing Machinery (ACM) digital library archive in scientific articles about the technological challenges of visualizing “large data sets,” this name appeared in October 1997.
In the early 2000s, the concept of “big data” gained momentum. The industry analyst Doug Laney defined big data as the three V’s:
- 1. Volume: Refers to the amount of data from different sources, for example, business transactions, social media, and information from account to account.
- 2. Velocity: Refers to the speed of data which must be dealt with it, for example, Radio-frequency identification (RFID tags2).
- 3. Variety: Refers to the different types of data, for example, numeric data, e-mail, video, audio, financial transactions, and stock ticker data.
Using big data helps many companies to increase their revenues. On the other hand, the lack of expertise in big data makes many SMEs fail to use it and benefit from it.
This chapter is focused on answering this question: How SME’s can use big data analytics to their advantage? In addition, to attempt this, we organized the chapter as follows: Section 5.2: Big data analytics. Section 5.3: Infrastructure for big data analytics. Section 5.4: The advantages of using big data analytics by SMEs. Section 5.5: Factors condition the poor adoption of business and big data analytics by SMEs.
