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Recent developments in data science ...
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Patnaik, Srikanta.
Recent developments in data science and business analyticsproceedings of the International Conference on Data Science and Business Analytics (ICDSBA- 2017) /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Recent developments in data science and business analyticsedited by Madjid Tavana, Srikanta Patnaik.
Reminder of title:
proceedings of the International Conference on Data Science and Business Analytics (ICDSBA- 2017) /
remainder title:
ICDSBA 2017
other author:
Tavana, Madjid.
Published:
Cham :Springer International Publishing :2018.
Description:
xvi, 505 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
ManagementStatistical methods
Online resource:
http://dx.doi.org/10.1007/978-3-319-72745-5
ISBN:
9783319727455$q(electronic bk.)
Recent developments in data science and business analyticsproceedings of the International Conference on Data Science and Business Analytics (ICDSBA- 2017) /
Recent developments in data science and business analytics
proceedings of the International Conference on Data Science and Business Analytics (ICDSBA- 2017) /[electronic resource] :ICDSBA 2017edited by Madjid Tavana, Srikanta Patnaik. - Cham :Springer International Publishing :2018. - xvi, 505 p. :ill., digital ;24 cm. - Springer proceedings in business and economics,2198-7246. - Springer proceedings in business and economics..
This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.
ISBN: 9783319727455$q(electronic bk.)
Standard No.: 10.1007/978-3-319-72745-5doiSubjects--Topical Terms:
809005
Management
--Statistical methods
LC Class. No.: HD30.215 / .R434 2018
Dewey Class. No.: 658.4013
Recent developments in data science and business analyticsproceedings of the International Conference on Data Science and Business Analytics (ICDSBA- 2017) /
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This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.
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EB HD30.215 .R295 2018 2018
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