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| Content Provider | ACM Digital Library |
|---|---|
| Author | Calitz, Andre Greyling, Jean Ayankoya, Kayode |
| Abstract | Data recording and storage have evolved over the past decades from manual gathering of data by using simple writing materials to the automation of data collection. Data storage has evolved significantly in the past decades and today databases no longer suffice as the only medium for the storage and management of data. This is due to the emergence of the Big Data and Data Science concepts. Previous studies have indicated that the multiplication of processing power of computers and the availability of larger data storage at reduced cost are part of the catalysts for the volume and rate at which data is now made available and captured. In this paper, the concepts of Big Data, Data Science and Business Analytics are reviewed. This paper discusses datafication of different aspects of life as the fundamental concept behind the growth of Big Data and Data Science. A review of the characteristics and value of Big Data and Data Science suggests that these emerging concepts will bring a paradigm change to a number of areas. Big Data was described as the basis for Data Science and Business Analytics which are tools employed in Data Science. Because these fields are still developing, there are diverse opinions, especially on the definition of Data Science. This paper provides a revised definition of Data Science, based on the review of available literature and proposes a schematic representation of the concepts. |
| Starting Page | 192 |
| Ending Page | 198 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781450332460 |
| DOI | 10.1145/2664591.2664619 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-09-29 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Business analytics Data science Big data Business intelligence Datafication |
| Content Type | Text |
| Resource Type | Article |
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