Integration challenges for analytics, business intelligence, and data mining:
"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" - Provided by publisher
Saved in:
| Other Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey PA, USA
IGI Global, Publisher of Timely Knowledge
[2021]
|
| Series: | A volume in the Advances in business information systems and analytics (ABISA) book series
Premier reference source |
| Subjects: | |
| Online Access: | DE-1050 DE-573 DE-898 DE-1049 DE-91 DE-706 DE-83 Volltext |
| Summary: | "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" - Provided by publisher |
| Physical Description: | 1 Online-Ressource (xix, 250 Seiten) Illustrationen |
| ISBN: | 9781799857839 |
| ISSN: | 2327-3283 |
| DOI: | 10.4018/978-1-7998-5781-5 |
Staff View
MARC
| LEADER | 00000nmm a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV047035806 | ||
| 003 | DE-604 | ||
| 005 | 20211210 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 201130s2021 |||| o||u| ||||||eng d | ||
| 020 | |a 9781799857839 |9 978-1-7998-5783-9 | ||
| 024 | 7 | |a 10.4018/978-1-7998-5781-5 |2 doi | |
| 035 | |a (ZDB-98-IGB)978-1-7998-5783-9 | ||
| 035 | |a (OCoLC)1225884351 | ||
| 035 | |a (DE-599)BVBBV047035806 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-1050 |a DE-706 |a DE-91 |a DE-898 |a DE-1049 |a DE-573 |a DE-83 | ||
| 245 | 1 | 0 | |a Integration challenges for analytics, business intelligence, and data mining |c Ana Azevedo (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal), Manuel Filipe Santos (Algoritmi Centre, University of Minho, Guimarães, Portugal) |
| 264 | 1 | |a Hershey PA, USA |b IGI Global, Publisher of Timely Knowledge |c [2021] | |
| 264 | 4 | |c © 2021 | |
| 300 | |a 1 Online-Ressource (xix, 250 Seiten) |b Illustrationen | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a A volume in the Advances in business information systems and analytics (ABISA) book series |x 2327-3283 | |
| 490 | 0 | |a Premier reference source | |
| 505 | 8 | |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 | |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" - Provided by publisher | ||
| 650 | 4 | |a Business enterprises / Data processing | |
| 650 | 4 | |a Business intelligence | |
| 650 | 4 | |a Data mining | |
| 650 | 7 | |a Business enterprises / Data processing |2 fast | |
| 650 | 7 | |a Business intelligence |2 fast | |
| 650 | 7 | |a Data mining |2 fast | |
| 700 | 1 | |a Azevedo, Ana |4 edt | |
| 700 | 1 | |a Santos, Manuel Filipe |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe, hardcover |z 978-1-7998-5781-5 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe, hardcover |z 1-7998-5781-6 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe, softcover |z 978-1-7998-5782-2 |
| 856 | 4 | 0 | |u https://doi.org/10.4018/978-1-7998-5781-5 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-98-IGB |a ZDB-1-IGE | ||
| 966 | e | |u https://doi.org/10.4018/978-1-7998-5781-5 |l DE-1050 |p ZDB-98-IGB |q FHD01_IGB_Kauf |x Verlag |3 Volltext | |
| 966 | e | |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5 |l DE-573 |p ZDB-1-IGE |x Verlag |3 Volltext | |
| 966 | e | |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5 |l DE-898 |p ZDB-1-IGE |x Verlag |3 Volltext | |
| 966 | e | |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5 |l DE-1049 |p ZDB-1-IGE |x Verlag |3 Volltext | |
| 966 | e | |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5 |l DE-91 |p ZDB-1-IGE |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.4018/978-1-7998-5781-5 |l DE-706 |p ZDB-98-IGB |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.4018/978-1-7998-5781-5 |l DE-83 |p ZDB-98-IGB |q TUB_EBS_IGB |x Verlag |3 Volltext | |
Record in the Search Index
| _version_ | 1805079031177019392 |
|---|---|
| adam_text | |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author2 | Azevedo, Ana Santos, Manuel Filipe |
| author2_role | edt edt |
| author2_variant | a a aa m f s mf mfs |
| author_facet | Azevedo, Ana Santos, Manuel Filipe |
| building | Verbundindex |
| bvnumber | BV047035806 |
| collection | ZDB-98-IGB ZDB-1-IGE |
| contents | 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 |
| ctrlnum | (ZDB-98-IGB)978-1-7998-5783-9 (OCoLC)1225884351 (DE-599)BVBBV047035806 |
| doi_str_mv | 10.4018/978-1-7998-5781-5 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nmm a2200000 c 4500</leader><controlfield tag="001">BV047035806</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20211210</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">201130s2021 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781799857839</subfield><subfield code="9">978-1-7998-5783-9</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4018/978-1-7998-5781-5</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-98-IGB)978-1-7998-5783-9</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1225884351</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047035806</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-1050</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-898</subfield><subfield code="a">DE-1049</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-83</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Integration challenges for analytics, business intelligence, and data mining</subfield><subfield code="c">Ana Azevedo (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal), Manuel Filipe Santos (Algoritmi Centre, University of Minho, Guimarães, Portugal)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hershey PA, USA</subfield><subfield code="b">IGI Global, Publisher of Timely Knowledge</subfield><subfield code="c">[2021]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xix, 250 Seiten)</subfield><subfield code="b">Illustrationen</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">A volume in the Advances in business information systems and analytics (ABISA) book series</subfield><subfield code="x">2327-3283</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Premier reference source</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="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</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="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" - Provided by publisher</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Business enterprises / Data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Business intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data mining</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Business enterprises / Data processing</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Business intelligence</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Data mining</subfield><subfield code="2">fast</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Azevedo, Ana</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Santos, Manuel Filipe</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe, hardcover</subfield><subfield code="z">978-1-7998-5781-5</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe, hardcover</subfield><subfield code="z">1-7998-5781-6</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe, softcover</subfield><subfield code="z">978-1-7998-5782-2</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.4018/978-1-7998-5781-5</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-98-IGB</subfield><subfield code="a">ZDB-1-IGE</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.4018/978-1-7998-5781-5</subfield><subfield code="l">DE-1050</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">FHD01_IGB_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5</subfield><subfield code="l">DE-573</subfield><subfield code="p">ZDB-1-IGE</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5</subfield><subfield code="l">DE-898</subfield><subfield code="p">ZDB-1-IGE</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5</subfield><subfield code="l">DE-1049</subfield><subfield code="p">ZDB-1-IGE</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-5781-5</subfield><subfield code="l">DE-91</subfield><subfield code="p">ZDB-1-IGE</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.4018/978-1-7998-5781-5</subfield><subfield code="l">DE-706</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.4018/978-1-7998-5781-5</subfield><subfield code="l">DE-83</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">TUB_EBS_IGB</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV047035806 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:03:47Z |
| indexdate | 2024-07-20T06:38:31Z |
| institution | BVB |
| isbn | 9781799857839 |
| issn | 2327-3283 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032442974 |
| oclc_num | 1225884351 |
| open_access_boolean | |
| owner | DE-1050 DE-706 DE-91 DE-BY-TUM DE-898 DE-BY-UBR DE-1049 DE-573 DE-83 |
| owner_facet | DE-1050 DE-706 DE-91 DE-BY-TUM DE-898 DE-BY-UBR DE-1049 DE-573 DE-83 |
| physical | 1 Online-Ressource (xix, 250 Seiten) Illustrationen |
| psigel | ZDB-98-IGB ZDB-1-IGE ZDB-98-IGB FHD01_IGB_Kauf ZDB-98-IGB TUB_EBS_IGB |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | IGI Global, Publisher of Timely Knowledge |
| record_format | marc |
| series2 | A volume in the Advances in business information systems and analytics (ABISA) book series Premier reference source |
| spelling | Integration challenges for analytics, business intelligence, and data mining Ana Azevedo (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal), Manuel Filipe Santos (Algoritmi Centre, University of Minho, Guimarães, Portugal) Hershey PA, USA IGI Global, Publisher of Timely Knowledge [2021] © 2021 1 Online-Ressource (xix, 250 Seiten) Illustrationen txt rdacontent c rdamedia cr rdacarrier A volume in the Advances in business information systems and analytics (ABISA) book series 2327-3283 Premier reference source 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" - Provided by publisher Business enterprises / Data processing Business intelligence Data mining Business enterprises / Data processing fast Business intelligence fast Data mining fast Azevedo, Ana edt Santos, Manuel Filipe edt Erscheint auch als Druck-Ausgabe, hardcover 978-1-7998-5781-5 Erscheint auch als Druck-Ausgabe, hardcover 1-7998-5781-6 Erscheint auch als Druck-Ausgabe, softcover 978-1-7998-5782-2 https://doi.org/10.4018/978-1-7998-5781-5 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Integration challenges for analytics, business intelligence, and data mining 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 Business enterprises / Data processing Business intelligence Data mining Business enterprises / Data processing fast Business intelligence fast Data mining fast |
| title | Integration challenges for analytics, business intelligence, and data mining |
| title_auth | Integration challenges for analytics, business intelligence, and data mining |
| title_exact_search | Integration challenges for analytics, business intelligence, and data mining |
| title_exact_search_txtP | Integration challenges for analytics, business intelligence, and data mining |
| title_full | Integration challenges for analytics, business intelligence, and data mining Ana Azevedo (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal), Manuel Filipe Santos (Algoritmi Centre, University of Minho, Guimarães, Portugal) |
| title_fullStr | Integration challenges for analytics, business intelligence, and data mining Ana Azevedo (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal), Manuel Filipe Santos (Algoritmi Centre, University of Minho, Guimarães, Portugal) |
| title_full_unstemmed | Integration challenges for analytics, business intelligence, and data mining Ana Azevedo (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal), Manuel Filipe Santos (Algoritmi Centre, University of Minho, Guimarães, Portugal) |
| title_short | Integration challenges for analytics, business intelligence, and data mining |
| title_sort | integration challenges for analytics business intelligence and data mining |
| topic | Business enterprises / Data processing Business intelligence Data mining Business enterprises / Data processing fast Business intelligence fast Data mining fast |
| topic_facet | Business enterprises / Data processing Business intelligence Data mining |
| url | https://doi.org/10.4018/978-1-7998-5781-5 |
| work_keys_str_mv | AT azevedoana integrationchallengesforanalyticsbusinessintelligenceanddatamining AT santosmanuelfilipe integrationchallengesforanalyticsbusinessintelligenceanddatamining |