Top

Published in:

2022 | OriginalPaper | Chapter

Datenvisualisierung und Business Intelligence – Methoden zur Unterstützung der Entscheidungsfindung

Author : Alec N. Sproten

Published in: Marketing Analytics

Publisher: Springer Fachmedien Wiesbaden

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Zusammenfassung

Eine zentrale Aufgabe innerhalb von Marketing Analytics ist es, Erkenntnisse aus Daten zu gewinnen, um die Entscheidungsfindung zu unterstützen. Business Intelligence und Visualisierung sind hierbei zwei stark verwandte, unerlässliche Werkzeuge. Business Intelligence (BI) stellt einen Methodenbaukasten bereit, um Daten systemseitig so zu kombinieren, dass möglichst treffgenau jeweils diejenigen Daten vorliegen, die für eine Entscheidung benötigt werden. Um die Effizienz der Entscheidungsfindung zu steigern, helfen Visualisierungen oft beim schnellen Erfassen der Daten. Dabei ist es wichtig, eine nutzerzentrierte Sicht bei der Entwicklung von Visualisierungen einzunehmen. Durch die Nutzerzentrierung werden die kognitiven Hürden zur Erfassung der Daten sowie die Exploration und Interaktion mit den Daten zu zentralen Säulen der Entscheidungsfindung. Dieser Beitrag gibt einen Einblick in die Anforderungen und Aufgaben, die eine BI-Lösung erfüllen muss, sowie in theoretische und praktische Grundlagen effizienter Visualisierungen, um die Entscheidungsfindung im Kontext des Marketings zu unterstützen.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Künstliche Intelligenz im Marketing

next chapter Mikrogeografische Marktsegmentierung

Abela, A. (2008). Advanced presentations by design: Creating communication that drives action. John Wiley & Sons.

Alhadad, S. S. (2018). Visualizing data to support judgement, inference, and decision making in learning analytics: Insights from cognitive psychology and visualization science. Journal of Learning Analytics, 5(2), 60–85.CrossRef

Anderson, B. A., & Yantis, S. (2013). Persistence of value-driven attentional capture. Journal of Experimental Psychology: Human Perception and Performance, 39(1), 6.

Ayres, P., & Sweller, J. (2005). The split-attention principle in multimedia learning. The Cambridge handbook of multimedia learning, 2, 135–146.

Bačić, D., & Fadlalla, A. (2016). Business information visualization intellectual contributions: An integrative framework of visualization capabilities and dimensions of visual intelligence. Decision Support Systems, 89, 77–86.CrossRef

Baker, J., Jones, D., & Burkman, J. (2009). Using visual representations of data to enhance sensemaking in data exploration tasks. Journal of the Association for Information Systems, 10(7), 2.CrossRef

Bertin, J. (2011). Semiology of graphics: Diagrams, networks, maps, Redlands. The University of Wisconsin Press.

Chiang, A. (28. November 2011). What Is a Dashboard? www.dashboardinsight.com/articles/digital-dashboards/fundamentals/what-is-a-dashboard.aspx. Zugegriffen: 30. Sep. 2020.

Cleveland, W. S. (1985). The elements of graphing data. Wadsworth Publ.

Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. (1999). Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. Journal of Experimental Psychology: General, 128(3), 309.CrossRef

Evelson, B., & Nicolson, N. (21. November 2008). Topic overview: Business Intelligence—An Information Workplace Report. Forrester. www.forrester.com/report/Topic+Overview+Business+Intelligence/-/E-RES39218. Zugegriffen: 30. Okt. 2020.

Few, S. (20. März 2004). Dashboard confusion. www.perceptualedge.com/articles/ie/dashboard_confusion.pdf Zugegriffen: 30. Sep. 2020.

Gartner (2010). Gartner outline the top 10 forces to impact outsourcing and it services industry. https://www.pressebox.com/pressrelease/gartner-uk-ltd/Gartner-Outlines-the-Top-10-Forces-to-Impact-Outsourcing-and-IT-Services-Industry/boxid/372008. Zugegriffen: 11. Apr. 2021

Gartner (2015a). Flipping to digital leadership. https://www.gartner.com/imagesrv/cio/pdf/cio_agenda_insights2015.pdf. Zugegriffen: 11. Apr. 2021

Gartner (2015b). Magic quadrant for advanced analytics platforms. https://www.gartner.com/en/documents/3204117/magic-quadrant-for-advanced-analytics-platforms. Zugegriffen: 11. Apr. 2021

Gobet, F. (2005). Chunking models of expertise: Implications for education. Applied Cognitive Psychology, 19(2), 183–204.CrossRef

Hamel, J. (2020). Worldwide business analytics services forecast, 2020–2024. IDC

Hannon, H. (2012). Kraft foods' recipe for successful business intelligence. SAPinsider.

Hegarty, M., Smallman, H. S., Stull, A. T., & Canham, M. S. (2009). Naïve cartography: How intuitions about display configuration can hurt performance. Cartographica: The International Journal for Geographic Information and Geovisualization, 44(3), 171–186.

Kosara, R., Hauser, H., & Gresh, D. L. (2003). An interaction view on information visualization. State-of-the-Art Report. Proceedings of EUROGRAPHICS, 123–137. https://kosara.net/papers/2003/Kosara-EG-2003.pdf. Zugegriffen: 11. Apr. 2021

Kosslyn, S. M. (1989). Understanding charts and graphs. Applied Cognitive Psychology, 3(3), 185–225.CrossRef

Kosslyn, S. M. (2006). Graph design for the eye and mind. OUP USA. Oxford University Press.CrossRef

Kursan, I., & Mihić, M. (2010). Business intelligence: The role of the internet in marketing research and business decision-making. Management: journal of contemporary management issues, 15(1), 69–86.

Liu, Z., & Stasko, J. (2010). Mental models, visual reasoning and interaction in information visualization: A top-down perspective. IEEE Transactions on Visualization and Computer Graphics, 16(6), 999–1008.CrossRef

MacKinlay, J., Hanrahan, P., & Stolte, C. (2007). Show me: Automatic presentation for visual analysis. IEEE Transactions on Visualization and Computer Graphics, 13(6), 1137–1144.CrossRef

Mansmann, S., & Scholl, M. H. (2008). Visual OLAP: A new paradigm for exploring multidimensional aggregates. In Proceedings of the IADIS International Conference on Computer Graphics and Visualization 2008 (CGV2 008) (S. 59–66). IADIS.

Matzen, L. E., Haass, M. J., Divis, K. M., & Stites, M. C. (July 2017). Patterns of attention: How data visualizations are read. In D. D. Schmorrow, & C. M. Fidopiastis (Hrsg.), Augmented Cognition. Neurocognition and Machine Learning (S. 176–191). Springer.

Mayer, R. E., & Fiorella, L. (2014). 12 principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In The Cambridge handbook of multimedia learning (Vol. 279). Cambridge University Press.

McCarthy, E. J., & Perreault, W. D., Jr. (1964). Basic Marketing. Richard D. Irwin.

McGrew, K. S. (2009). CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence, 37, 1–10.CrossRef

Michal, A. L., & Franconeri, S. L. (2017). Visual routines are associated with specific graph interpretations. Cognitive Research: Principles and Implications, 2(1), 1–10.

Miller, S. J., Hickson, D. J., & Wilson, D. C. (1996). Decision-making in organizations. Reprinted. In G. Salaman (Hrsg.). (2002), Decision making for business (S. 74–93). Sage.

Okan, Y., Galesic, M., & Garcia-Retamero, R. (2016). How people with low and high graph literacy process health graphs: Evidence from eye-tracking. Journal of Behavioral Decision Making, 29(2–3), 271–294.CrossRef

Ranjan, J. (2008). Business justification with business intelligence. Vine, 38(4), 461–475.CrossRef

Rosenholtz, R., Li, Y., & Nakano, L. (2007). Measuring visual clutter. Journal of Vision, 7(2), 17–17.CrossRef

Saama (2015). Saama Teams up With Tableau to Deliver Advanced Analytics to Insurance, High-Tech, CPG, Life Sciences and Healthcare Customers. https://www.businesswire.com/news/home/20150331005276/en/Saama-Teams-Up-With-Tableau-to-Deliver-Advanced-Analytics-to-Insurance-High-Tech-CPG-Life-Sciences-and-Healthcare-Customers. Zugegriffen: 11. Apr. 2021.

Savoska, S., & Loshkovska, S. (2014). Taxonomy of user intention and benefits of visualization for financial and accounting data analysis. ICT Innovations 2013 (S. 197–207). Springer.CrossRef

Shah, P. (1997). A model of the cognitive and perceptual processes in graphical display comprehension. Reasoning with diagrammatic representations. Journal of Experimental Psychology: Applied, 4(2) 94–101.

Shah, P., & Freedman, E. G. (2011). Bar and line graph comprehension: An interaction of top-down and bottom-up processes. Topics in Cognitive Science, 3(3), 560–578.CrossRef

Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings 1996 IEEE symposium on visual languages (S. 336–343). IEEE.

Smallman, H. S., & St. John, M. . (2005). Naïve realism: Misplaced faith in realistic displays. Ergonomics in Design, 13(3), 6–13.CrossRef

Sun, Z., Sun, L., & Strang, K. (2018). Big data analytics services for enhancing business intelligence. Journal of Computer Information Systems, 58(2), 162–169.CrossRef

Sweller, J., Van Merrienboer, J. J., & Paas, F. G. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.CrossRef

Theeuwes, J. (2010). Top–down and bottom–up control of visual selection. Acta Psychologica, 135(2), 77–99.CrossRef

Tufte, E. R. (2006). Beautiful evidence. Graphis Press.

Tufte, E. R., & Graves-Morris, P. R. (1983). The visual display of quantitative information (Vol. 2, No. 9). Graphics press.

Tufte, E. R., Goeler, N. H., & Benson, R. (1990). Envisioning information (Bd. 126). Graphics press.

Tufte, E. R., McKay, S. R., Christian, W., & Matey, J. R. (1998). Visual explanations: Images and quantities, evidence and narrative. Graphics press.

Tukey, J. W. (1977). Exploratory data analysis (Bd. 2). Pearson.

Wang, H., & Wang, S. (2008). A knowledge management approach to data mining process for business intelligence. Industrial Management & Data Systems, 108(5), 622–634.CrossRef

Winter, T., & Zimmermann, U. T. (2000). Real-time dispatch of trams in storage yards. Annals of Operations Research, 96(1–4), 287–315.CrossRef

Wixom, B. H., Watson, H. J., Reynolds, A. M., & Hoffer, J. A. (2008). Continental airlines continues to soar with business intelligence. Information Systems Management, 25(2), 102–112.CrossRef

Yi, J. S., ah Kang, Y., Stasko, J., & Jacko, J. A. (2007). Toward a deeper understanding of the role of interaction in information visualization. IEEE transactions on visualization and computer graphics, 13(6), 1224–1231.

Zacks, J., Levy, E., Tversky, B., & Schiano, D. J. (1998). Reading bar graphs: Effects of extraneous depth cues and graphical context. Journal of Experimental Psychology: Applied, 4(2), 119.

Zheng, J. G. (2017). Data visualization for business intelligence. In M. Munoz (Hrsg.), Global Business Intelligence (S. 67–82). Taylor & Francis.CrossRef

Zheng, G., Zheng, C., & Li, L. (2019). Bringing business intelligence to health information technology curriculum. Journal of Information Systems Education, 25(4), 6.

Title: Datenvisualisierung und Business Intelligence – Methoden zur Unterstützung der Entscheidungsfindung
Author: Alec N. Sproten
Publisher: Springer Fachmedien Wiesbaden
Book: Marketing Analytics
Print ISBN: 978-3-658-33808-4

Electronic ISBN: 978-3-658-33809-1

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-3-658-33809-1_8