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Feature Influence Based ETL for Efficient Big Data Management

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Field Value
 
Title Feature Influence Based ETL for Efficient Big Data Management
 
Creator Vijayalakshmi, M
Minu, R I
 
Subject Cloud
FSII
FSSI
FIA
NCTS
Ontology
 
Description 1310-1316
The increased volume of big data introduces various challenges for its maintenance and analysis. There exist various
approaches to the problem, but they fail to achieve the expected results. To improve the big data management performance,
an efficient real time feature influence analysis based Extraction, Transform, and Loading (ETL) framework is presented in
this article. The model fetches the big data and analyses the features to find noisy records by preprocessing the data set.
Further, the method performs feature extraction and applies feature influence analysis to various data nodes and the data
present in the data nodes. The method estimates Feature Specific Informative Influence (FSII) and Feature Specific
Supportive Influence (FSSI). The value of FSII and FSSI are measured with the support of a data dictionary. The class
ontology belongs to various classes of data. The value of FSII is measured according to the presence of a concrete feature on
a tuple towards any data node, whereas the value of FSSI is measured based on the appearance of supportive features on any
data point towards the data node. Using these measures, the method computes the Node Centric Transformation Score
(NCTS). Based on the value of NCTS the method performs map reduction and merging of data nodes. The NCTS_FIA
method achieves higher performance in the ETL process. By adapting feature influence analysis in big data management,
the ETL performance is improved with the least amount of time complexity.
 
Date 2022-12-07T11:36:48Z
2022-12-07T11:36:48Z
2022-12
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/61002
https://doi.org/10.56042/jsir.v81i12.54992
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source JSIR Vol.81(12) [December 2022]