Data Warehouse & Data Mining:
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Deutsch |
| Veröffentlicht: |
Herdecke [u.a.]
W3L-Verl.
2009
|
| Schriftenreihe: | Informatik
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016291244&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | VIII, 234 S. graph. Darst. |
| ISBN: | 3937137661 9783937137667 |
Internformat
MARC
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|---|---|---|---|
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| 003 | DE-604 | ||
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| 020 | |a 3937137661 |9 3-937137-66-1 | ||
| 020 | |a 9783937137667 |9 978-3-937137-66-7 | ||
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| 084 | |a DAT 620f |2 stub | ||
| 100 | 1 | |a Gabriel, Roland |d 1947- |e Verfasser |0 (DE-588)133149005 |4 aut | |
| 245 | 1 | 0 | |a Data Warehouse & Data Mining |c Roland Gabriel ; Peter Gluchowski ; Alexander Pastwa |
| 264 | 1 | |a Herdecke [u.a.] |b W3L-Verl. |c 2009 | |
| 300 | |a VIII, 234 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Informatik | |
| 650 | 0 | 7 | |a Data-Warehouse-Konzept |0 (DE-588)4406462-7 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Data Mining |0 (DE-588)4428654-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Business Intelligence |0 (DE-588)4588307-5 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Data-Warehouse-Konzept |0 (DE-588)4406462-7 |D s |
| 689 | 0 | 1 | |a Data Mining |0 (DE-588)4428654-5 |D s |
| 689 | 0 | 2 | |a Business Intelligence |0 (DE-588)4588307-5 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Gluchowski, Peter |d 1962- |e Verfasser |0 (DE-588)133257428 |4 aut | |
| 700 | 1 | |a Pastwa, Alexander |d 1976- |e Verfasser |0 (DE-588)124284248 |4 aut | |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016291244&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-016291244 | |
Datensatz im Suchindex
| DE-BY-TUM_call_number | 0002 DAT 620f 2013 A 2877 |
|---|---|
| DE-BY-TUM_katkey | 1927703 |
| DE-BY-TUM_location | 00 |
| DE-BY-TUM_media_number | 040007790756 |
| _version_ | 1821933075193397249 |
| adam_text | VII
Inhalt
1 Einleitung *.............................................................. 1
1.1 Einordnung und Abgrenzung *................................. 1
1.1.1 Betriebliche
Informations-
und
Kommunikationssysteme - Arten und
Integrationsrichtungen *........................................... 2
1.1.2 Data
Warehouse
als integrierte Datenbasis
analyseorientierter Informationssysteme *................ 6
1.1.3 OLAP*...................................................................... 10
1.1.4 Data Mining *........................................................... 12
1.2 Historische Entwicklung *........................................ 16
1.2.1
MIS
- Management Information -Systeme **............... 20
1.2.2 DSS-
Decision
Support-Systeme **........................... 24
1.2.3 EIS- Executive Information- Systeme **.................... 28
1.2.4
ESS
- Executive Support-Systeme **.......................... 33
1.3
Fallstudie: TOPBIKE
**.............................................. 35
2 Data
Warehouse
und OLAP*.................................. 41
2.1 Grundlagen *............................................................
4Î
2.1.1 Einordnung und Komponenten des Data Warehouse-
Konzeptes *.............................................................. 43
2.1.1.1 Data IVareftouse-Architekturen und -Komponenten * 45
2.1.1.2 Prozesse zum Extrahieren, Transformieren und
Laden von Daten **................................................... 49
2.1.2 OLAP - On-Line
Analytical Processing
*..................... 52
2.1.2.1 Die zwölf OLAP-Evaluierungsregeln *....................... 54
2.1.2.2 Multidimensionalität durch die Verwendung von
Datenwürfein *......................................................... 57
2.1.2.3 Speicherkonzepte für OLAP-Lösungen **................... 59
2.1.2.4 Navigation in multidimensionalen Datenstrukturen * 60
2.1.2.5 Frontend-Techniken und -Funktionen*..................... 61
2.1.3 Vorgehensmodell zur Gestaltung
multidimensionaler Informationssysteme **.............. 65
2.1.4 Einsatzbereiche multidimensionaler
Informationssysteme *.............................................. 69
2.2 Modellierung und Implementierung **...................... 73
2.2.1 Bestandteile multidimensionaler Datenstrukturen **. 74
2.2.2 Gestaltung multidimensionaler Datenstrukturen
bzw. modeile **....................................................... 78
2.2.3 Semantische Modellierung **.................................... 81
2.2.4 Implementierung mit multidimensionalen
Datenbanksystemen **............................................. 90
2.2.5 Implementierung mit relationalen
Datenbanksystemen **............................................. 93
VIH
Inhalt
3
3.
3.
.1
3.
.2
3.
1.3
3.
1.3.1
3.
1.3.2
3.
1.3.3
3.
1.3.4
3.
1.3.5
3.
1.3.6
3.
1.4
2.3
Fallstudie: TOPBIKE
-
BI
**......................................... 102
Data Mining
-
Datenmustererkennung
*................ 115
Grundlagen des Data Mining
*.................................. 116
Treiber des
Data Mining
*......................................... 116
Auslegungen zum
Data Mining
*.............................. 120
Das CRISP-DM-Modell *............................................. 123
Überblick über das CRISP-DM-Modell *...................... 124
Business
Understanding
*......................................... 125
Data
Understanding
-Auswahl und Sichtung der
Daten *..................................................................... 127
Data
Preparation
- Datenaufbereitung *.................... 128
Data
Modeling
- Anwendung der Data Mining-
Verfahren *............................................................... 134
Evaluation und
Deployment
*................................... 138
Betriebswirtschaftliche Einsatzgebiete des Data
Mining *................................................................... 1 39
3.1.5 Web Mining und Text Mining als alternative
Analyseansätze **.................................................... 142
3.2 Ausgewählte Methoden des Data Mining ***............. 144
3.2.1 Künstliche Neuronale Netze ***................................ 145
3.2.2 Entscheidungsbaumverfahren ***............................. 151
3.2.3 Clusterverfahren ***................................................. 1 56
3.2.4 Verfahren zur Assoziationsanalyse ***...................... 161
3.3 Fallstudie: TOPBIKE - Data Mining **......................... 165
3.3.1
Fallstudie:
TOPBIKE - Business
Understanding
(Phasel) **................................................................ 166
3.3.2 Fallstudie: TOPBIKE - Data
Understanding
(Phase
2) **......................................................................... 1 74
3.3.3 Fallstudie: TOPBIKE - Data
Preparation
(Phase 3) **... 180
3.3.4 Fallstudie: TOPBIKE - Data
Modeling
(Phase 4) **...... 185
3.3.5 Fallstudie: TOPBIKE - Evaluation und
Deployment
(Phase 5 und Phase 6) **........................................... 205
4 Zusammenfassung und Ausblick **....................... 209
Glossar...................................................................................... 215
Literatur.................................................................................... 225
Sachindex.................................................................................. 232
|
| any_adam_object | 1 |
| author | Gabriel, Roland 1947- Gluchowski, Peter 1962- Pastwa, Alexander 1976- |
| author_GND | (DE-588)133149005 (DE-588)133257428 (DE-588)124284248 |
| author_facet | Gabriel, Roland 1947- Gluchowski, Peter 1962- Pastwa, Alexander 1976- |
| author_role | aut aut aut |
| author_sort | Gabriel, Roland 1947- |
| author_variant | r g rg p g pg a p ap |
| building | Verbundindex |
| bvnumber | BV023088343 |
| classification_rvk | QP 345 ST 530 |
| classification_tum | WIR 640f DAT 620f |
| ctrlnum | (OCoLC)436274468 (DE-599)BVBBV023088343 |
| dewey-full | 658.40380285574 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.40380285574 |
| dewey-search | 658.40380285574 |
| dewey-sort | 3658.40380285574 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Informatik Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV023088343 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T13:08:21Z |
| institution | BVB |
| isbn | 3937137661 9783937137667 |
| language | German |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016291244 |
| oclc_num | 436274468 |
| open_access_boolean | |
| owner | DE-M347 DE-355 DE-BY-UBR DE-859 DE-523 DE-473 DE-BY-UBG DE-634 DE-Eb1 DE-384 DE-12 DE-1049 DE-19 DE-BY-UBM DE-858 DE-573 DE-863 DE-BY-FWS DE-2070s DE-91 DE-BY-TUM DE-N2 DE-521 |
| owner_facet | DE-M347 DE-355 DE-BY-UBR DE-859 DE-523 DE-473 DE-BY-UBG DE-634 DE-Eb1 DE-384 DE-12 DE-1049 DE-19 DE-BY-UBM DE-858 DE-573 DE-863 DE-BY-FWS DE-2070s DE-91 DE-BY-TUM DE-N2 DE-521 |
| physical | VIII, 234 S. graph. Darst. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | W3L-Verl. |
| record_format | marc |
| series2 | Informatik |
| spellingShingle | Gabriel, Roland 1947- Gluchowski, Peter 1962- Pastwa, Alexander 1976- Data Warehouse & Data Mining Data-Warehouse-Konzept (DE-588)4406462-7 gnd Data Mining (DE-588)4428654-5 gnd Business Intelligence (DE-588)4588307-5 gnd |
| subject_GND | (DE-588)4406462-7 (DE-588)4428654-5 (DE-588)4588307-5 |
| title | Data Warehouse & Data Mining |
| title_auth | Data Warehouse & Data Mining |
| title_exact_search | Data Warehouse & Data Mining |
| title_full | Data Warehouse & Data Mining Roland Gabriel ; Peter Gluchowski ; Alexander Pastwa |
| title_fullStr | Data Warehouse & Data Mining Roland Gabriel ; Peter Gluchowski ; Alexander Pastwa |
| title_full_unstemmed | Data Warehouse & Data Mining Roland Gabriel ; Peter Gluchowski ; Alexander Pastwa |
| title_short | Data Warehouse & Data Mining |
| title_sort | data warehouse data mining |
| topic | Data-Warehouse-Konzept (DE-588)4406462-7 gnd Data Mining (DE-588)4428654-5 gnd Business Intelligence (DE-588)4588307-5 gnd |
| topic_facet | Data-Warehouse-Konzept Data Mining Business Intelligence |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016291244&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT gabrielroland datawarehousedatamining AT gluchowskipeter datawarehousedatamining AT pastwaalexander datawarehousedatamining |
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Teilbibliothek Stammgelände
| Signatur: |
0002 DAT 620f 2013 A 2877
Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |