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Utilizing big data paradigms for bus...

Darmont, J{acute}er{circ}ome, (1972-)

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Utilizing big data paradigms for business intelligence

Record Type:	Electronic resources : Monograph/item
Title/Author:	Utilizing big data paradigms for business intelligence/ Jerome Darmont and Sabine Loudcher, editors.
other author:	Darmont, J{acute}er{circ}ome,
Published:	Hershey, Pennsylvania :IGI Global, : [2018],
Description:	1 online resource (xxii, 313 p.)
Notes:	Includes index.
[NT 15003449]:	Chapter 1. Applications of artificial intelligence in the realm of business intelligence -- Chapter 2. A big data platform for enhancing life imaging activities -- Chapter 3. A Survey of parallel indexing techniques for large-scale moving object databases -- Chapter 4. Privacy and security in data-driven urban mobility -- Chapter 5. C-idea: a fast algorithm for computing emerging closed datacubes -- Chapter 6. Large multivariate time series forecasting: Survey on methods and scalability -- Chapter 7. Exploring multiple dynamic social networks in computer-mediated communications: an experimentally validated ecosystem -- Chapter 8. Analysis of operation performance of blast furnace with machine learning methods.
Subject:	Business intelligence - Data processing. -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-4963-5
ISBN:	9781522549642 (ebook)

Utilizing big data paradigms for business intelligence
Utilizing big data paradigms for business intelligence[electronic resource] /Jerome Darmont and Sabine Loudcher, editors. - Hershey, Pennsylvania :IGI Global,[2018] - 1 online resource (xxii, 313 p.)

Includes index.

Includes bibliographical references and index.

Chapter 1. Applications of artificial intelligence in the realm of business intelligence -- Chapter 2. A big data platform for enhancing life imaging activities -- Chapter 3. A Survey of parallel indexing techniques for large-scale moving object databases -- Chapter 4. Privacy and security in data-driven urban mobility -- Chapter 5. C-idea: a fast algorithm for computing emerging closed datacubes -- Chapter 6. Large multivariate time series forecasting: Survey on methods and scalability -- Chapter 7. Exploring multiple dynamic social networks in computer-mediated communications: an experimentally validated ecosystem -- Chapter 8. Analysis of operation performance of blast furnace with machine learning methods.

Restricted to subscribers or individual electronic text purchasers.

"This book explores problems related to the five "Vs" of big data, technological issues, as well as big data analytics applications. It also covers how data must be extracted, grouped, organized, aggregated and correlated with methods and techniques such as data integration (ETL), data warehousing, online analytical processing (OLAP), reporting, data mining and machine learning"--Provided by publisher.

ISBN: 9781522549642 (ebook)Subjects--Topical Terms:

884808
Business intelligence
--Data processing.

LC Class. No.: HD38.7 / .U75 2018e

Dewey Class. No.: 658.4/72028557

Utilizing big data paradigms for business intelligence
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050 0 0 $a HD38.7 $b .U75 2018e
082 0 0 $a 658.4/72028557 $2 23
245 0 0 $a Utilizing big data paradigms for business intelligence $h [electronic resource] / $c Jerome Darmont and Sabine Loudcher, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2018]
300 $a 1 online resource (xxii, 313 p.)
500 $a Includes index.
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Applications of artificial intelligence in the realm of business intelligence -- Chapter 2. A big data platform for enhancing life imaging activities -- Chapter 3. A Survey of parallel indexing techniques for large-scale moving object databases -- Chapter 4. Privacy and security in data-driven urban mobility -- Chapter 5. C-idea: a fast algorithm for computing emerging closed datacubes -- Chapter 6. Large multivariate time series forecasting: Survey on methods and scalability -- Chapter 7. Exploring multiple dynamic social networks in computer-mediated communications: an experimentally validated ecosystem -- Chapter 8. Analysis of operation performance of blast furnace with machine learning methods.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book explores problems related to the five "Vs" of big data, technological issues, as well as big data analytics applications. It also covers how data must be extracted, grouped, organized, aggregated and correlated with methods and techniques such as data integration (ETL), data warehousing, online analytical processing (OLAP), reporting, data mining and machine learning"--Provided by publisher.
650 0 $a Business intelligence $x Data processing. $3 884808
650 0 $a Big data. $3 2045508
700 1 $a Darmont, J{acute}er{circ}ome, $d 1972- $e editor. $3 3395581
700 1 $a Loudcher, Sabine, $d 1969- $e editor. $3 3395582
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-4963-5