Big Data Analytics Services for Enhancing Business Intelligence

Sun, Zhaohao; Sun, Lili; Strang, Kenneth David

doi:10.1080/08874417.2016.1220239

Cited by 133 publications

(69 citation statements)

References 16 publications

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“…Through subjective understanding and interpretive analysis, I gathered from studies such as Sun et al (2018), Gandomi and Haider (2015) and LaValle et al (2011) that an understanding of big data analytics and getting substantial value for organisational purposes is more than the mere use of software tools. It first requires an understanding of the main factors, which can deterministically affect the outcome.…”

Section: Analysis and Discussion: Understanding Big Data Analyticsmentioning

confidence: 99%

“…However, Gandomi and Haider (2015) suggest that by using big data analytic tools, massive volumes of semi-structured data can be mined to improve service delivery and competiveness. Thus, individual or combined analytic tools, such as the descriptive, prescriptives and predictive, are employed to guide various types of decisionmaking (Sun, Sun & Strang 2018). However, that does not seem to solve the challenges of the holistic and in-depth extraction of useful elements from big data (Zakir et al 2015).…”

Section: Big Data Analytics In Organisationsmentioning

confidence: 99%

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A multilevel approach to big data analysis using analytic tools and actor network theory

Iyamu

2018

S. Afr. j. inf. manag.

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Background: Over the years, big data analytics has been statically carried out in a programmed way, which does not allow for translation of data sets from a subjective perspective. This approach affects an understanding of why and how data sets manifest themselves into various forms in the way that they do. This has a negative impact on the accuracy, redundancy and usefulness of data sets, which in turn affects the value of operations and the competitive effectiveness of an organisation. Also, the current single approach lacks a detailed examination of data sets, which big data deserve in order to improve purposefulness and usefulness.Objective: The purpose of this study was to propose a multilevel approach to big data analysis. This includes examining how a sociotechnical theory, the actor network theory (ANT), can be complementarily used with analytic tools for big data analysis.Method: In the study, the qualitative methods were employed from the interpretivist approach perspective.Results: From the findings, a framework that offers big data analytics at two levels, micro- (strategic) and macro- (operational) levels, was developed. Based on the framework, a model was developed, which can be used to guide the analysis of heterogeneous data sets that exist within networks.Conclusion: The multilevel approach ensures a fully detailed analysis, which is intended to increase accuracy, reduce redundancy and put the manipulation and manifestation of data sets into perspectives for improved organisations’ competitiveness.

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Section: Analysis and Discussion: Understanding Big Data Analyticsmentioning

confidence: 99%

Section: Big Data Analytics In Organisationsmentioning

confidence: 99%

A multilevel approach to big data analysis using analytic tools and actor network theory

Iyamu

2018

S. Afr. j. inf. manag.

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“…Big data analysis was defined as the process of collecting, organizing and analyzing large data to discover, visualize, display of patterns, knowledge, intelligence, and other information within big data [7]. The study [8] shows that organizations use analytical tools in the field of marketing, communications, retail, and audit to discover the potential opportunities in big data, there are many tools and techniques used to analyze such data: Hadoop, MapReduce, NoSQL, Grid Gain, HPCC, Storm, Sap Hana, and Cassandra.…”

Section: The Concept Of Big Data Types and Characteristicsmentioning

confidence: 99%

“…Studies [7][8][9][10][11][12][13][14] have shown the importance of Big Data analysis as follows: Provides a highly competitive advantage for enterprises, rationalize decision-making, Contribute to give a comprehensive overview of the company, and develop a business strategy, Supports integrated reporting more effectively, using both financial and non-financial information to disclose the company's performance, Helps to improve risk management, and discover opportunities to reduce costs. Big Data analytics helps companies better understand customer behavior to increase customer satisfaction, increase business efficiency, increase sales, and increase opportunities for innovation in process and product development.…”

Section: The Importance Of Big Datamentioning

confidence: 99%

Big Data and the Future of the Accounting Profession

Younis¹

2020

IJST

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Background/objectives: The purpose of this research is to study and analyze the Big Data, to identify the challenges which facing Big Data in business organizations, and to clarify the impact of Big Data on changing the roles of accountants and accounting profession. Determining the impact of big data analysis on improvement accounting information quality. Methods/statistical analysis: To achieve this objective, reference was made to previous studies and related research, with a qualitative study based on in-depth and semi-structured interviews with specialists in the field of accounting and data analysis. Findings: The study concluded the impact of big data on the roles of accountants and the profession of accounting in the future, the importance of big data analysis in improving the accounting information quality. Improvements/applications: The other main findings of this research are that the importance to teach Big Data and business analysis in the curriculum of accounting education at the university level to enhance students' knowledge on the importance of such data and how to process, store, and use them in the accounting field. The study recommends carrying out further scientific and applied research in Big Data to know its impact on the developments of the accounting profession. Originality/ value: The original contribution of the study lies in the empirical investigation of the phenomenon of Big Data and the extent of the need for it because it provides great opportunities in the field of accounting measurement, changing the roles of accountants, the development of the accounting profession, and improving the quality of accounting information as one of the most recent developments in the accounting context.

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“…Big data has become a very popular expression in recent years, related to the advance of technology which allows, on the one hand, the recovery of a great amount of data, and on the other hand, the analysis of that data, benefiting from the increasing computational capacity of devices. Big data has been used in several research areas such as business intelligence (Chen et al 2012;Sun et al 2018), marketing (Verhoef et al 2015;Wright et al 2019), economics (Glaeser et al 2018;Sobolevsky et al 2017), health (Pramanik et al 2017;Rose et al 2019), and psychology (Matz and Netzer 2017;Adjerid and Kelley 2018), among many other areas and studies which could be mentioned.…”

Section: Introductionmentioning

confidence: 99%

From Big Data to Econophysics and Its Use to Explain Complex Phenomena

Ferreira

Pereira

2020

JRFM

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Big data has become a very frequent research topic, due to the increase in data availability. In this introductory paper, we make the linkage between the use of big data and Econophysics, a research field which uses a large amount of data and deals with complex systems. Different approaches such as power laws and complex networks are discussed, as possible frameworks to analyze complex phenomena that could be studied using Econophysics and resorting to big data.

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Big Data Analytics Services for Enhancing Business Intelligence

Cited by 133 publications

References 16 publications

A multilevel approach to big data analysis using analytic tools and actor network theory

A multilevel approach to big data analysis using analytic tools and actor network theory

Big Data and the Future of the Accounting Profession

From Big Data to Econophysics and Its Use to Explain Complex Phenomena

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