scholarly journals Novel Incremental Ranking Framework for Biomedical Data Analytics and Dimensionality Reduction: Big Data Challenges and Opportunities

2015 ◽  
Vol 8 (4) ◽  
Keyword(s):  
Big Data ◽  
Dimensionality Reduction ◽  
Data Analytics ◽  
Biomedical Data ◽  
Challenges And Opportunities

Overview of Big Data and Its Visualization

2022 ◽  
pp. 22-53
Author(s):  
Richard S. Segall ◽  
Gao Niu
Keyword(s):  
Big Data ◽  
Traffic Safety ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Real Data ◽  
Flow Diagram ◽  
Data Sets ◽  
United States Department ◽  
Big Data Visualization ◽  
Challenges And Opportunities

Big Data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. This chapter discusses what Big Data is and its characteristics, and how this information revolution of Big Data is transforming our lives and the new technology and methodologies that have been developed to process data of these huge dimensionalities. This chapter discusses the components of the Big Data stack interface, categories of Big Data analytics software and platforms, descriptions of the top 20 Big Data analytics software. Big Data visualization techniques are discussed with real data from fatality analysis reporting system (FARS) managed by National Highway Traffic Safety Administration (NHTSA) of the United States Department of Transportation. Big Data web-based visualization software are discussed that are both JavaScript-based and user-interface-based. This chapter also discusses the challenges and opportunities of using Big Data and presents a flow diagram of the 30 chapters within this handbook.

Relevance of big data to forensic accounting practice and education

2019 ◽  
Vol 34 (3) ◽  
pp. 268-288 ◽  
Author(s):  
Zabihollah Rezaee ◽  
Jim Wang
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Accounting Education ◽  
Content Type ◽  
Accounting Practice ◽  
Accounting Curriculum ◽  
Forensic Accounting ◽  
Accounting Courses ◽  
Challenges And Opportunities ◽  
Practical Implications

Purpose This paper aims to examine the relevance of Big Data to forensic accounting practice and education by gathering opinions from a sample of academics and practitioners in China. Design/methodology/approach The authors conduct a survey of academics and practitioners regarding the desired demand, importance and content of Big Data educational skills and topics for forensic accounting education to effectively respond to challenges and opportunities in the age of Big Data. Findings Results indicate that the demand for and interest in Big Data/data analytics and forensic accounting will continue to increase; Big Data/data analytics and forensic accounting should be integrated into the business curriculum; many of the suggested Big Data topics should be integrated into forensic accounting education; and some attributes and techniques of Big Data are important in improving forensic accounting education and practice. Research limitations/implications Readers should interpret the results with caution because of the sample size (95 academics and 103 practitioners) and responses obtained from academics and practitioners in one country (China) that may not be representative of the global population. Practical implications The results are useful in integrating Big Data topics into the forensic accounting curriculum and in redesigning the forensic accounting courses/programs. Social implications The results have implications for forensic accountants in effectively fulfilling their responsibilities to their profession and society by combating fraud. Originality/value This study provides educational, research and practical implications as Big Data and forensic accounting are advancing.

Big Data Analytics for Predictive Maintenance Modeling: Challenges and Opportunities

2015 ◽  
Author(s):  
I. H. F. Santos ◽  
M. M. Machado ◽  
E. E. Russo ◽  
D. M. Manguinho ◽  
V. T. Almeida ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Predictive Maintenance ◽  
Challenges And Opportunities
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