The Goal-oriented Business Intelligence Architectures Method : A Process-based Approach to Combine Traditional and Novel Analytical Technologies

An abundance of new analytics technologies emerged since the advent of the Big Data trend and enabled new Business Intelligence (BI) use cases, which were not possible with traditional technologies. While Data Warehouses were the primary choice for traditional BI architectures, the technology select...

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Weiterer Titel:The GOBIA Method
Verfasser: Fekete, David
Weitere Beteiligte: Vossen, Gottfried (Gutachter)
FB/Einrichtung:FB 04: Wirtschaftswissenschaftliche Fakultät
Dokumenttypen:Dissertation/Habilitation
Medientypen:Text
Erscheinungsdatum:2020
Publikation in MIAMI:22.06.2020
Datum der letzten Änderung:25.06.2020
Reihe:Wissenschaftliche Schriften der Universität Münster / Reihe IV, Bd. 18
Verlag/Hrsg.: readbox unipress in der readbox publishing GmbH
Angaben zur Ausgabe:[Electronic ed.]
Schlagwörter:business intelligence; architectures; goal-oriented; big data; technology selection; analytics Business Intelligence; Architekturen; ziel-orientiert; Big Data; Technologieauswahl; Analytics
Fachgebiet (DDC):000: Informatik, Wissen, Systeme
Lizenz:CC BY 4.0
Sprache:English
Hochschulschriftenvermerk:Zugl.: Münster (Westfalen), Univ., Diss., 2018
Anmerkungen:Auch im Buchhandel erhältlich: The Goal-oriented Business Intelligence Architectures Method : A Process-based Approach to Combine Traditional and Novel Analytical Technologies / David Fekete. – Dortmund : readbox unipress, 2020. – xv, 530 S. (Wissenschaftliche Schriften der WWU Münster : Reihe IV ; Bd. 18), ISBN 978-3-8405-0226-2, Preis: 38,50 EUR
Format:PDF-Dokument
ISBN:978-3-8405-0226-2
URN:urn:nbn:de:hbz:6-11169662922
Permalink:https://nbn-resolving.de/urn:nbn:de:hbz:6-11169662922
Onlinezugriff:diss_fekete_buchblock.pdf
Inhaltsverzeichnis:
  • 1 Introduction ..... 1
  • 1.1 Motivation ..... 1
  • 1.2 Structure and Research Method ..... 6
  • 1.3 FROG AIR Sample Case ..... 15
  • 2 Background ..... 17
  • 2.1 Traditional Business Intelligence ..... 17
  • 2.1.1 Relational Database Management Systems and SQL ..... 21
  • 2.1.2 Data Warehouses ..... 31
  • 2.2 Big Data Technologies ..... 50
  • 2.2.1 Big Data Phenomenon and Characteristics ..... 50
  • 2.2.2 NoSQL Data Stores ..... 61
  • 2.2.3 Hadoop Distributed File System (HDFS) ..... 72
  • 2.2.4 MapReduce ..... 79
  • 2.2.5 Hadoop Ecosystem ..... 86
  • 2.2.6 Stream Processing ..... 89
  • 2.2.7 Advancements to Traditional Technologies ..... 107
  • 2.3 Big Data Analytics ..... 110
  • 2.3.1 Analytics in the Big Data Age ..... 110
  • 2.3.2 Machine Learning ..... 114
  • 2.3.3 Methods ..... 118
  • 2.3.4 New Analytics Domains ..... 124
  • 2.4 Process Modeling ..... 129
  • 2.5 Requirements Engineering ..... 132
  • 2.5.1 Goals ..... 136
  • 2.5.2 Requirements ..... 137
  • 2.5.3 System Development Approaches ..... 141
  • 2.5.4 FROG AIR Case Example ..... 142
  • 2.6 Multi-Perspective Architecture Analysis ..... 149
  • 2.6.1 Methods for Strategic Analysis ..... 149
  • 2.6.2 TORE Analysis Framework ..... 152
  • 3 Analytical Architectures in Research and Practice ..... 155
  • 3.1 Architectures Background ..... 156
  • 3.2 Big Data Value Chains ..... 164
  • 3.2.1 Analysis of Existing Value Chains ..... 165
  • 3.2.2 A Unified Big Data Value Chain ..... 173
  • 3.3 Data Warehouse Architecture Advancements ..... 178
  • 3.3.1 Data Warehouse 2.0 by Inmon ..... 179
  • 3.3.2 Data Warehouses and Big Data ..... 180
  • 3.4 Big Data Reference Architectures ..... 183
  • 3.4.1 Big Data Reference Architecture by Paakkonen and Pakkala ..... 184
  • 3.4.2 NIST Big Data Reference Architecture ..... 189
  • 3.4.3 Big Data Solution Reference Architecture by Geerdink ..... 197
  • 3.4.4 Oracle Big Data Platform ..... 201
  • 3.4.5 Lambda Architecture by Marz and Warren ..... 206
  • 3.4.6 SOLID Architecture by Martinez-Prieto et al. ..... 211
  • 3.4.7 Analysis ..... 214
  • 3.5 Big Data Architectures in Practice ..... 222
  • 3.6 Selection Criteria for Analytical Architectures ..... 230
  • 3.7 Solution Artifact Requirements ..... 234
  • 3.7.1 Solution and Design Principles ..... 235
  • 3.7.2 Requirements Overview ..... 238
  • 4 Goal-oriented Business Intelligence Architectures (GOBIA) Method ..... 241
  • 4.1 Overview of the Approach ..... 242
  • 4.1.1 Design Approach ..... 244
  • 4.1.2 Method Scope ..... 247
  • 4.1.3 Execution in Cycles ..... 252
  • 4.2 GOBIA.REF ..... 253
  • 4.2.1 Functional Reference Architecture ..... 254
  • 4.2.2 Technological Reference Architecture ..... 259
  • 4.3 GOBIA.DEV ..... 272
  • 4.3.1 Phase I ..... 273
  • 4.3.2 Phase II ..... 288
  • 4.3.3 Phase III ..... 298
  • 4.4 Post-GOBIA Activities ..... 318
  • 4.5 Extending the GOBIA Method ..... 322
  • 4.5.1 Updating the GOBIA Tool Repository ..... 323
  • 4.5.2 Updating GOBIA.REF ..... 331
  • 4.5.3 Updating GOBIA.DEV ..... 333
  • 5 Evaluation ..... 337
  • 5.1 Evaluation Method ..... 337
  • 5.2 Selected Case Applications ..... 339
  • 5.2.1 Stream Analytics: Hospital Asset Management ..... 340
  • 5.2.2 Advanced Analytics: Housing Price Prediction ..... 368
  • 5.2.3 Big Data Analytics: Plagiarism Checking ..... 383
  • 5.3 Evaluation Results Discussion ..... 397
  • 5.3.1 Summary of Results ..... 397
  • 5.3.2 Reflection on the Solution Artifact Requirements ..... 400
  • 6 Discussion ..... 407
  • 7 Conclusion ..... 411
  • 7.1 Summary ..... 411
  • 7.2 Outlook ..... 415
  • Bibliography ..... 419
  • List of Web Pages ..... 447
  • List of Abbreviations ..... 485
  • A Architecture Literature Search Details ..... 491
  • B Supplementary GOBIA Models ..... 497
  • C GOBIA Tool Repository ..... 507
  • C.1 Tool Lists ..... 507
  • C.1.1 Data Acquisition ..... 508
  • C.1.2 Data Storage ..... 509
  • C.1.3 Data Processing ...... 513
  • C.1.4 Data Analytics ..... 513
  • C.2 Compatibility Matrix ..... 519.

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