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Integration challenges for analytics, business intelligence, and data mining[electronic resource] /

レコード種別:	コンピュータ・メディア : 単行資料
[NT 15000414] null:	658.4/72
タイトル / 著者:	Integration challenges for analytics, business intelligence, and data mining/ Ana Azevedo and Manuel Filipe Santos, editors.
その他の著者:	Azevedo, Ana.
出版された:	Hershey, Pennsylvania : : IGI Global,, 2020.
記述:	1 online resource (xix, 250 p.)
主題:	Business enterprises - Data processing.
主題:	Business intelligence.
主題:	Data mining.
国際標準図書番号 (ISBN) :	9781799857839 (ebk.)
国際標準図書番号 (ISBN) :	9781799857815 (hbk.)
国際標準図書番号 (ISBN) :	9781799857822 (pbk.)
[NT 15000227] null:	Includes bibliographical references and index.
[NT 15000228] null:	Section 1. Background and literature review. Chapter 1. Data mining and business intelligence: a bibliometric analysis ; Chapter 2. Integration of data mining and business intelligence in big data analytics: a research agenda on scholarly publications ; Chapter 3. From business intelligence to big data: the power of analytics -- Section 2. Big data issues. Chapter 4. Big data quality for data mining in business intelligence applications: current state and research directions ; Chapter 5. Enterprise data lake management in business intelligence and analytics: challenges and research gaps in analytics practices and integration -- Section 3. Modelling issues. Chapter 6. Modelling in support of decision making in business intelligence ; Chapter 7. Causal feature selection ; Chapter 8. K-nearest neighbors algorithm (KNN): an approach to detect illicit transaction in the bitcoin network -- Section 4. Software and security. Chapter 9. A framework to evaluate big data fabric tools ; Chapter 10. A novel approach using steganography and cryptography in business intelligence.
[NT 15000229] null:	"This book provides insights concerning the integration of data mining in business intelligence and analytics systems, increasing the understanding of using data mining in the context of business intelligence and analytics"--
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5

Integration challenges for analytics, business intelligence, and data mining[electronic resource] /
Integration challenges for analytics, business intelligence, and data mining[electronic resource] /Ana Azevedo and Manuel Filipe Santos, editors. - Hershey, Pennsylvania :IGI Global,2020. - 1 online resource (xix, 250 p.)

Includes bibliographical references and index.

Section 1. Background and literature review. Chapter 1. Data mining and business intelligence: a bibliometric analysis ; Chapter 2. Integration of data mining and business intelligence in big data analytics: a research agenda on scholarly publications ; Chapter 3. From business intelligence to big data: the power of analytics -- Section 2. Big data issues. Chapter 4. Big data quality for data mining in business intelligence applications: current state and research directions ; Chapter 5. Enterprise data lake management in business intelligence and analytics: challenges and research gaps in analytics practices and integration -- Section 3. Modelling issues. Chapter 6. Modelling in support of decision making in business intelligence ; Chapter 7. Causal feature selection ; Chapter 8. K-nearest neighbors algorithm (KNN): an approach to detect illicit transaction in the bitcoin network -- Section 4. Software and security. Chapter 9. A framework to evaluate big data fabric tools ; Chapter 10. A novel approach using steganography and cryptography in business intelligence.

"This book provides insights concerning the integration of data mining in business intelligence and analytics systems, increasing the understanding of using data mining in the context of business intelligence and analytics"--

ISBN: 9781799857839 (ebk.)Subjects--Topical Terms:

341439
Business enterprises
--Data processing.

LC Class. No.: HF5548.2 / .I58 2020

Dewey Class. No.: 658.4/72

Integration challenges for analytics, business intelligence, and data mining[electronic resource] /
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006 m o d
007 cr cn
008 230513s2020 pau fob 001 0 eng d
020 $a 9781799857839 (ebk.)
020 $a 9781799857815 (hbk.)
020 $a 9781799857822 (pbk.)
035 $a (OCoLC)1224336025
035 $a 1101012310
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
050 0 0 $a HF5548.2 $b .I58 2020
082 0 0 $a 658.4/72 $2 23
245 0 0 $a Integration challenges for analytics, business intelligence, and data mining $h [electronic resource] / $c Ana Azevedo and Manuel Filipe Santos, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2020.
300 $a 1 online resource (xix, 250 p.)
504 $a Includes bibliographical references and index.
505 0 $a Section 1. Background and literature review. Chapter 1. Data mining and business intelligence: a bibliometric analysis ; Chapter 2. Integration of data mining and business intelligence in big data analytics: a research agenda on scholarly publications ; Chapter 3. From business intelligence to big data: the power of analytics -- Section 2. Big data issues. Chapter 4. Big data quality for data mining in business intelligence applications: current state and research directions ; Chapter 5. Enterprise data lake management in business intelligence and analytics: challenges and research gaps in analytics practices and integration -- Section 3. Modelling issues. Chapter 6. Modelling in support of decision making in business intelligence ; Chapter 7. Causal feature selection ; Chapter 8. K-nearest neighbors algorithm (KNN): an approach to detect illicit transaction in the bitcoin network -- Section 4. Software and security. Chapter 9. A framework to evaluate big data fabric tools ; Chapter 10. A novel approach using steganography and cryptography in business intelligence.
520 3 $a "This book provides insights concerning the integration of data mining in business intelligence and analytics systems, increasing the understanding of using data mining in the context of business intelligence and analytics"-- $c Provided by publisher.
650 0 $a Business enterprises $x Data processing. $3 341439
650 0 $a Business intelligence. $3 189092
650 0 $a Data mining. $3 337740
700 1 $a Azevedo, Ana. $3 750511
700 1 $a Santos, Manuel Filipe. $3 750512
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5

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