An Analysis of Software Parallelism in Big Data Technologies for Data-Intensive Architectures

2021 ◽  
pp. 181-188
Author(s):  
Felipe Cerezo ◽  
Carlos E. Cuesta ◽  
Belén Vela
Keyword(s):  
Big Data ◽  
Data Intensive ◽  
Big Data Technologies

Big Data Technologies and Management

2018 ◽  
pp. 196-210
Author(s):  
Jayashree K. ◽  
Abirami R.
Keyword(s):  
Big Data ◽  
Large Scale ◽  
New Paradigm ◽  
It Industry ◽  
Data Intensive ◽  
Big Data Technologies ◽  
Data Explosion ◽  
Business Engineering ◽  
Future Direction ◽  
Big Data Computing

Developments in information technology and its prevalent growth in several areas of business, engineering, medical, and scientific studies are resulting in information as well as data explosion. Knowledge discovery and decision making from such rapidly growing voluminous data are a challenging task in terms of data organization and processing, which is an emerging trend known as big data computing. Big data has gained much attention from the academia and the IT industry. A new paradigm that combines large-scale compute, new data-intensive techniques, and mathematical models to build data analytics. Thus, this chapter discusses the background of big data. It also discusses the various application of big data in detail. The various related work and the future direction would be addressed in this chapter.

Big Data Technologies and Management

2022 ◽  
pp. 1734-1744
Author(s):  
Jayashree K. ◽  
Abirami R.
Keyword(s):  
Big Data ◽  
Large Scale ◽  
New Paradigm ◽  
It Industry ◽  
Data Intensive ◽  
Big Data Technologies ◽  
Data Explosion ◽  
Business Engineering ◽  
Future Direction ◽  
Big Data Computing

Developments in information technology and its prevalent growth in several areas of business, engineering, medical, and scientific studies are resulting in information as well as data explosion. Knowledge discovery and decision making from such rapidly growing voluminous data are a challenging task in terms of data organization and processing, which is an emerging trend known as big data computing. Big data has gained much attention from the academia and the IT industry. A new paradigm that combines large-scale compute, new data-intensive techniques, and mathematical models to build data analytics. Thus, this chapter discusses the background of big data. It also discusses the various application of big data in detail. The various related work and the future direction would be addressed in this chapter.

A Fitting Approach to Construct and Measurement Alignment

2017 ◽  
Vol 21 (3) ◽  
pp. 592-632 ◽  
Author(s):  
Margaret M. Luciano ◽  
John E. Mathieu ◽  
Semin Park ◽  
Scott I. Tannenbaum
Keyword(s):  
Big Data ◽  
Data Streams ◽  
Iterative Process ◽  
Emerging Technologies ◽  
Measurement Techniques ◽  
Great Promise ◽  
Big Data Technologies ◽  
Nearly Continuous ◽  
Dynamic Phenomena ◽  
Over Time

Many phenomena of interest to management and psychology scholars are dynamic and change over time. One of the primary impediments to the examination of dynamic phenomena has been challenges associated with collecting data at a sufficient frequency and duration to accurately model such changes. Emerging technologies that produce nearly continuous streams of big data offer great promise to address those challenges; however, they introduce new methodological challenges and construct validity concerns. We seek to integrate the emerging big data technologies into the existing repertoire of measurement techniques and advance an iterative process to enhance their measurement fit. First, we provide an overview of dynamic constructs and temporal frameworks, highlighting their measurement implications. Second, we discuss different data streams and feature emerging technologies that leverage big data as a means to index dynamic constructs. Third, we integrate the previous sections and advance an iterative approach to achieving measurement fit, highlighting factors that make some measurement choices more suitable and viable than others. In so doing, we hope to accelerate the advancement of dynamic theories and methods.

scholarly journals Lists of Ethical, Legal, Societal and Economic Issues of Big Data Technologies

2017 ◽  
Author(s):  
Bart Custers ◽  
Karolina La Fors ◽  
Magdalena Jozwiak ◽  
Keymolen Esther ◽  
Daniel Bachlechner ◽  
...  
Keyword(s):  
Big Data ◽  
Economic Issues ◽  
Big Data Technologies
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