TY  - JOUR
T1  - Parallel Processing for Data Mining and Data Analysis Applications
AU - Moattar, Mohammad H. AU - Taharozi, Maziyar AU - Yazdi, Samira Arabi AU - Rekavandi, Sodabeh Salehi 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 5
SP  - 1228
EP  - 1234
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.1228.1234
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.1228.1234
KW  - Data mining
KW  -parallel
KW  -procedure
KW  -map
KW  -sharding
KW  -reduce
AB  - This study emphasize on how parallelism can be applied in data analysis. In recent decades where
the large amount of data is produced by machines: software logs, cameras, microphones, RFIDs, etc. Creation
speed rate of these data will increase exponentially with Moore’s Law. Saving or storing such amount of data
is inexpensive and using some parallel processing methods, the data can also be investigated and mined
effectively. So, this study intends to debate about parallel programming procedures used in data analysis and
data mining. The key motive for this parallelism is to make analysis more rapidly. This is generally attained by
using multiple processors or multiple computers, execution dissimilar aspects of data analysis or mining,
performing the tasks alongside and later consolidating the data into a single report.
ER  -