An Accounting Information Systems Perspective on Data Analytics and Big Data

2017 ◽  
Vol 31 (3) ◽  
pp. 101-114 ◽  
Author(s):  
Esperanza Huerta ◽  
Scott Jensen
Keyword(s):  
Big Data ◽  
Information Systems ◽  
Data Analytics ◽  
Accounting Information ◽  
Security Requirements ◽  
Future Research ◽  
Accounting Information Systems ◽  
Systems Perspective ◽  
Analytic Skills

ABSTRACT Forty-six academics and practitioners participated in the second Journal of Information Systems Conference to discuss data analytics and Big Data from an accounting information systems perspective. The panels discussed the evolving role of technology in accounting, privacy within the domain of Big Data, and people and Big Data. Throughout all three panels, several topics emerged that impact all areas of accounting—developing enhanced analytical and data handling skills; evaluating privacy, security requirements, and risks; thinking creatively; and assessing the threat of automation to the accounting profession. Other topics were specific to a segment of the profession, such as the growing demand for privacy compliance audits and the curriculum adjustments necessary to develop data analytic skills. This commentary synthesizes and expands the discussions of the conference panels and suggests potential areas for future research.

scholarly journals THE IMPACT OF BIG DATA ANALYTICS ON IMPROVING FINANCIAL REPORTING QUALITY

2020 ◽  
Vol 4 (03) ◽  
Author(s):  
Nagat Mohamed Marie Younis
Keyword(s):  
Big Data ◽  
Financial Reporting ◽  
Data Analytics ◽  
Information Quality ◽  
Accounting Information ◽  
Big Data Analytics ◽  
Reporting Quality ◽  
Financial Reporting Quality ◽  
Accounting Information Quality ◽  
The Impact

Purpose – The current study aims to clarify the importance of big data analytics and its role in changing the accounting profession and the roles of accountants, in addition to testing the impact of big data analytics on improving financial reporting quality in the Saudi environment. Design/ methodology/ approach – To achieve the study's goals and validate hypotheses, relevant previous literature and research are referred. Also, a field study is conducted by distributing a questionnaire of (154) individual academics, financial analysts, accountants, and experts in the field of analyzing big data in the Kingdom of Saudi in 2019. Data are analyzed by using the program of Statistical Package for Social Science (SPSS 17.0). Findings – The study concluded that although business organizations face several challenges when analyzing data, big data analytics has a significant role in achieving high competitiveness for institutions, improving the accounting information quality, providing appropriate information that helps in rationalizing decisions within the economic unit, and providing future information affecting stakeholder's decisions. The study also has proved that there is a statistically significant effect of big data analytics on improving the quality of accounting information, as big data analytics clearly affects the characteristics of the accounting information quality, positively affecting the quality of financial reports. Originality/ Value – Originality/ Value – The analytics of big data is one of the most important topics where it positively affects the improvement of accounting information quality, which reflects on financial reporting quality. Hence, academics and institutions should pay attention to this topic and follow their new ideas. The present study is one of the first studies that deal with this topic and examine the relationship between big data analytics and the characteristics of accounting information which positively affecting financial reporting quality.

An REA Ontology-Based Model for Mapping Big Data to Accounting Information Systems Elements

2017 ◽  
Vol 31 (3) ◽  
pp. 45-61 ◽  
Author(s):  
Uday S. Murthy ◽  
Guido L. Geerts
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Information Systems ◽  
Accounting Information ◽  
Data Sources ◽  
Complex Data ◽  
Accounting Information Systems ◽  
Business Transaction ◽  
Business Transactions ◽  
Data Elements

ABSTRACT The term “Big Data” refers to massive volumes of data that grow at an increasing rate and encompass complex data types such as audio and video. While the applications of Big Data and analytic techniques for business purposes have received considerable attention, it is less clear how external sources of Big Data relate to the transaction processing-oriented world of accounting information systems. This paper uses the Resource-Event-Agent Enterprise Ontology (REA) (McCarthy 1982; International Standards Organization [ISO] 2007) to model the implications of external Big Data sources on business transactions. The five-phase REA-based specification of a business transaction as defined in ISO (2007) is used to formally define associations between specific Big Data elements and business transactions. Using Big Data technologies such as Apache Hadoop and MapReduce, a number of information extraction patterns are specified for extracting business transaction-related information from Big Data. We also present a number of analytics patterns to demonstrate how decision making in accounting can benefit from integrating specific external Big Data sources and conventional transactional data. The model and techniques presented in this paper can be used by organizations to formalize the associations between external Big Data elements in their environment and their accounting information artifacts, to build architectures that extract information from external Big Data sources for use in an accounting context, and to leverage the power of analytics for more effective decision making.

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