Abstract
This study aims to review the challenges of implementing big data analytics by Small and Medium Enterprises (SMES) in Malaysia. There is a lack of literature studies examining the relationship betw...
Highlights
Big data consist of huge datasets, whereby the size of these datasets often exceeds the collection, management, use, and processing capabilities of human beings in an acceptable time
128,000 full-text articles excluded based on the following: -within 5 years (125,480) -not related to challenges of big data (10,0000) -not related to SMEs
This study examines the relationship between the legal, architecture, social, and market factors that pose a challenge to Malaysia SMEs
Summary
Big data consist of huge datasets, whereby the size of these datasets often exceeds the collection, management, use, and processing capabilities of human beings in an acceptable time. The scale of big data is always changing. In 2001, Doug Laney, an META Group ( Gartner) analyst, noted that the challenges and opportunities of data growth consist of three directions, namely volume (volume, data size), velocity (velocity, data input and output speed), and changeability (variety, diversity), collectively referred to as “3 V” or “3 Vs”. Gartner and most companies in the big data industry continue to use 3V to describe big data. In 2012, the definition of big data was revised by Gartner as follows: “Big data is a large, high-speed, and/or changeable information asset. Some organisations have defined the fourth V characteristic known as Veracity
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