Big-Data Analysis of Process Performance: A Case Study of Smart Cities

2018 ◽  
pp. 41-63
Author(s):  
Alejandro Vera-Baquero ◽  
Ricardo Colomo-Palacios
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Smart Cities ◽  
Big Data Analysis ◽  
Process Performance

Data Science and Big Data Analytics in Financial Services

Web Services ◽  
2019 ◽  
pp. 1301-1329
Author(s):  
Suren Behari ◽  
Aileen Cater-Steel ◽  
Jeffrey Soar
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Financial Services ◽  
Data Science ◽  
Big Data Analytics ◽  
Disruptive Innovation ◽  
Big Data Analysis ◽  
Future Trends ◽  
The Right

The chapter discusses how Financial Services organizations can take advantage of Big Data analysis for disruptive innovation through examination of a case study in the financial services industry. Popular tools for Big Data Analysis are discussed and the challenges of big data are explored as well as how these challenges can be met. The work of Hayes-Roth in Valued Information at the Right Time (VIRT) and how it applies to the case study is examined. Boyd's model of Observe, Orient, Decide, and Act (OODA) is explained in relation to disruptive innovation in financial services. Future trends in big data analysis in the financial services domain are explored.

Big Data Analysis for Retrofit Projects in Smart Cities

2019 ◽  
Author(s):  
Haiyan Xie ◽  
Wei Shi ◽  
Harshit Choudhary ◽  
Hanliang Fu ◽  
Xiaotong Guo
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Smart Cities ◽  
Big Data Analysis

scholarly journals Enhancing Big Data Analysis by using Map-reduce Technique

2018 ◽  
Vol 7 (1) ◽  
pp. 113-116
Author(s):  
Alaa Hussein Al-Hamami ◽  
Ali Adel Flayyih
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Response Time ◽  
Data Analytics ◽  
Big Data Analysis ◽  
Map Reduce ◽  
Fast Method ◽  
Traditional Methods ◽  
Electroencephalogram Eeg

Database is defined as a set of data that is organized and distributed in a manner that permits the user to access the data being stored in an easy and more convenient manner. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work enhances the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on Electroencephalogram (EEG) Big-data as a case study. The proposed approach showed clear enhancement on managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG researchers and specialist with an easy and fast method of handling the EEG big data.

scholarly journals Can Big Data Analysis Make Cities Smarter? Emerging Issues and Stakeholder Implications in Smart Mobility

2017 ◽  
Vol 8 (1) ◽  
pp. 23 ◽  
Author(s):  
Asst. Prof. Dr. Serkan Gürsoy ◽  
Asst. Prof. Dr. Murat Yücelen
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Smart Cities ◽  
Academic Research ◽  
Big Data Analysis ◽  
Ongoing Debate ◽  
Research Fields ◽  
Emerging Issues ◽  
Smart Mobility ◽  
Applied Fields

This study deals with the challenges and bottlenecks with respect to the concept of smart cities which has largely been constructed on knowledge utilization issues and challenges. Despite the abundant existent literature in this field, the effective transformation of data into knowledge which can become a source of competitive advantage is still an ongoing debate, especially due to contemporary developments in big data analysis methods, approaches and strategies. As an emerging problem, the derivation of significant meaning from big data is among popular academic research fields, as well as being a crucial industrial and policy making engagement regarding value creating mechanisms in smart cities. Therefore in this study, limitations and challenges in translating big data into valuable knowledge in academia and industries are considered within the concept of smart mobility. In an attempt to propose researchers, business firms and governmental entities a collaborative approach, a perception about emerging issues is presented for clarifying some future constructs intersecting in relevant research and applied fields.

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