Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature

The importance of data science and big data analytics is growing very fast as organizations are gearing up to leverage their information assets to gain competitive advantage. The flexibility offered through big data analytics empowers functional as well as firm-level performance. In the first phase...

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Veröffentlicht in:Global journal of flexible systems management Jg. 18; H. 3; S. 203 - 229
Hauptverfasser: Grover, Purva, Kar, Arpan Kumar
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New Delhi Springer India 01.09.2017
Nature Publishing Group
Schlagworte:
Big Data
Business and Management
Data analysis
Data mining
Data warehouses
Information management
Original Article
Programming languages
Social networks
Studies
Data science
Big data
Big data technologies
Information management
Systematic literature review
ISSN:0972-2696, 0974-0198
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Abstract The importance of data science and big data analytics is growing very fast as organizations are gearing up to leverage their information assets to gain competitive advantage. The flexibility offered through big data analytics empowers functional as well as firm-level performance. In the first phase of the study, we attempt to analyze the research on big data published in high-quality business management journals. The analysis was visualized using tools for big data and text mining to understand the dominant themes and how they are connected. Subsequently, an industry-specific categorization of the studies was done to understand the key use cases. It was found that most of the existing research focuses majorly on consumer discretionary, followed by public administration. Methodologically, a major focus in such exploration is in social media analytics, text mining and machine learning applications for meeting objectives in marketing and supply chain management. However, it was found that not much focus was highlighted in these studies to demonstrate the tools used for the analysis. To address this gap, this study also discusses the evolution, types and usage of big data tools. The brief overview of big data technologies grouped by the services they enable and some of their applications are presented. The study categorizes these tools into big data analysis platforms, databases and data warehouses, programming languages, search tools, and data aggregation and transfer tools. Finally, based on the review, future directions for exploration in big data has been provided for academic and practice.
AbstractList The importance of data science and big data analytics is growing very fast as organizations are gearing up to leverage their information assets to gain competitive advantage. The flexibility offered through big data analytics empowers functional as well as firm-level performance. In the first phase of the study, we attempt to analyze the research on big data published in high-quality business management journals. The analysis was visualized using tools for big data and text mining to understand the dominant themes and how they are connected. Subsequently, an industry-specific categorization of the studies was done to understand the key use cases. It was found that most of the existing research focuses majorly on consumer discretionary, followed by public administration. Methodologically, a major focus in such exploration is in social media analytics, text mining and machine learning applications for meeting objectives in marketing and supply chain management. However, it was found that not much focus was highlighted in these studies to demonstrate the tools used for the analysis. To address this gap, this study also discusses the evolution, types and usage of big data tools. The brief overview of big data technologies grouped by the services they enable and some of their applications are presented. The study categorizes these tools into big data analysis platforms, databases and data warehouses, programming languages, search tools, and data aggregation and transfer tools. Finally, based on the review, future directions for exploration in big data has been provided for academic and practice.
The importance of data science and big data analytics is growing very fast as organizations are gearing up to leverage their information assets to gain competitive advantage. The flexibility offered through big data analytics empowers functional as well as firm-level performance. In the first phase of the study, we attempt to analyze the research on big data published in high-quality business management journals. The analysis was visualized using tools for big data and text mining to understand the dominant themes and how they are connected. Subsequently, an industry-specific categorization of the studies was done to understand the key use cases. It was found that most of the existing research focuses majorly on consumer discretionary, followed by public administration. Methodologically, a major focus in such exploration is in social media analytics, text mining and machine learning applications for meeting objectives in marketing and supply chain management. However, it was found that not much focus was highlighted in these studies to demonstrate the tools used for the analysis. To address this gap, this study also discusses the evolution, types and usage of big data tools. The brief overview of big data technologies grouped by the services they enable and some of their applications are presented. The study categorizes these tools into big data analysis platforms, databases and data warehouses, programming languages, search tools, and data aggregation and transfer tools. Finally, based on the review, future directions for exploration in big data has been provided for academic and practice.
Author Kar, Arpan Kumar
Grover, Purva
Author_xml – sequence: 1
  givenname: Purva
  orcidid: 0000-0001-5191-891X
  surname: Grover
  fullname: Grover, Purva
  email: groverdpurva@gmail.com
  organization: Information Systems Area, DMS, Indian Institute of Technology Delhi
– sequence: 2
  givenname: Arpan Kumar
  surname: Kar
  fullname: Kar, Arpan Kumar
  organization: Information Systems Area, DMS, Indian Institute of Technology Delhi
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crossref_primary_10_1007_s40171_017_0159_3
crossref_citationtrail_10_1007_s40171_017_0159_3
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PublicationCentury 2000
PublicationDate 20170900
2017-9-00
20170901
PublicationDateYYYYMMDD 2017-09-01
PublicationDate_xml – month: 9
  year: 2017
  text: 20170900
PublicationDecade 2010
PublicationPlace New Delhi
PublicationPlace_xml – name: New Delhi
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PublicationTitle Global journal of flexible systems management
PublicationTitleAbbrev Glob J Flex Syst Manag
PublicationYear 2017
Publisher Springer India
Nature Publishing Group
Publisher_xml – name: Springer India
– name: Nature Publishing Group
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SubjectTerms Big Data
Business and Management
Data analysis
Data mining
Data warehouses
Information management
Original Article
Programming languages
Social networks
Studies
Title Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature
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