Big Data Analytics Correlation Taxonomy
Big data analytics (BDA) is an increasingly popular research area for both organisations and academia due to its usefulness in facilitating human understanding and communication. In the literature, researchers have focused on classifying big data according to data type, data security or level of dif...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-12-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/11/1/17 |
| _version_ | 1828516973178257408 |
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| author | Laden Husamaldin Nagham Saeed |
| author_facet | Laden Husamaldin Nagham Saeed |
| author_sort | Laden Husamaldin |
| collection | DOAJ |
| description | Big data analytics (BDA) is an increasingly popular research area for both organisations and academia due to its usefulness in facilitating human understanding and communication. In the literature, researchers have focused on classifying big data according to data type, data security or level of difficulty, and many research papers reveal that there is a lack of information on evidence of a real-world link of big data analytics methods and its associated techniques. Thus, many organisations are still struggling to realise the actual value of big data analytic methods and its associated techniques. Therefore, this paper gives a design research account for formulating and proposing a step ahead to understand the relation between the analytical methods and its associated techniques. Furthermore, this paper is an attempt to clarify this uncertainty and identify the difference between analytics methods and techniques by giving clear definitions for each method and its associated techniques to integrate them later in a new correlation taxonomy based on the research approaches. Thus, the primary outcome of this research is to achieve for the first time a correlation taxonomy combining analytic methods used for big data and its recommended techniques that are compatible for various sectors. This investigation was done through studying various descriptive articles of big data analytics methods and its associated techniques in different industries. |
| first_indexed | 2024-12-11T18:34:26Z |
| format | Article |
| id | doaj.art-55a601ae327740ce8c70b49a4b9f61ca |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-12-11T18:34:26Z |
| publishDate | 2019-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-55a601ae327740ce8c70b49a4b9f61ca2022-12-22T00:54:48ZengMDPI AGInformation2078-24892019-12-011111710.3390/info11010017info11010017Big Data Analytics Correlation TaxonomyLaden Husamaldin0Nagham Saeed1School of Computing and Engineering, University of West London, London W5 5RF, UKSchool of Computing and Engineering, University of West London, London W5 5RF, UKBig data analytics (BDA) is an increasingly popular research area for both organisations and academia due to its usefulness in facilitating human understanding and communication. In the literature, researchers have focused on classifying big data according to data type, data security or level of difficulty, and many research papers reveal that there is a lack of information on evidence of a real-world link of big data analytics methods and its associated techniques. Thus, many organisations are still struggling to realise the actual value of big data analytic methods and its associated techniques. Therefore, this paper gives a design research account for formulating and proposing a step ahead to understand the relation between the analytical methods and its associated techniques. Furthermore, this paper is an attempt to clarify this uncertainty and identify the difference between analytics methods and techniques by giving clear definitions for each method and its associated techniques to integrate them later in a new correlation taxonomy based on the research approaches. Thus, the primary outcome of this research is to achieve for the first time a correlation taxonomy combining analytic methods used for big data and its recommended techniques that are compatible for various sectors. This investigation was done through studying various descriptive articles of big data analytics methods and its associated techniques in different industries.https://www.mdpi.com/2078-2489/11/1/17big data analytics methodsbig data characteristicsbig data techniquesbig data correlation taxonomy |
| spellingShingle | Laden Husamaldin Nagham Saeed Big Data Analytics Correlation Taxonomy Information big data analytics methods big data characteristics big data techniques big data correlation taxonomy |
| title | Big Data Analytics Correlation Taxonomy |
| title_full | Big Data Analytics Correlation Taxonomy |
| title_fullStr | Big Data Analytics Correlation Taxonomy |
| title_full_unstemmed | Big Data Analytics Correlation Taxonomy |
| title_short | Big Data Analytics Correlation Taxonomy |
| title_sort | big data analytics correlation taxonomy |
| topic | big data analytics methods big data characteristics big data techniques big data correlation taxonomy |
| url | https://www.mdpi.com/2078-2489/11/1/17 |
| work_keys_str_mv | AT ladenhusamaldin bigdataanalyticscorrelationtaxonomy AT naghamsaeed bigdataanalyticscorrelationtaxonomy |