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Data Extraction and Exploration Tools for Business Intelligence

  • Mário Cardoso
  • Tiago Guimarães
  • Carlos Filipe Portela
  • Manuel Filipe SantosEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1041)

Abstract

Business intelligence (BI) has undergone constant changes currently, due to the increasing emergence of new technologies, which are introduced to improve the processes inherent in decision-making in organizations. However, not all users are familiar with the tools of a typical BI system, so there is a heavy reliance on the assistance of information technology (IT) technicians in the area of data extraction and exploitation (DEE), for ad hoc analyses. In this article, we intend to analyze some DEE tools on the market and their applicability to resolve and help these user’s issues in their work environment. For this purpose, literature survey of these type of users and their requirements was done; six DEE tools were selected, analyzed, and experimented; a topology was defined to evaluate the DEE tools in order to identify the one that best applies to business data extraction and exploitation from data warehouses and data marts, associated with BI system and responds to the requirements of these users.

Keywords

Business intelligence Data analytics Data extraction Data exploration 

Notes

Acknowledgements

This article is a result of the project Deus Ex Machina: NORTE-01-0145-FEDER-000026, supported by Norte Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF).

References

  1. 1.
    R.L. Ackoff, From data to wisdom. J. Appl. Syst. Anal. 16(1), 3–9 (1989). http://doi.org/citeulike-article-id:6930744
  2. 2.
    G. Bellinger, D. Castro, A. Mills, Data, Information, Knowledge, and Wisdom (2004), pp. 5–7Google Scholar
  3. 3.
    T.H. Davenport, L. Prusak, Working knowledge—how organizations manage what they know. 21(8), 395–403 (Harvard Business School Press, Boston Massachusetts, 2000)Google Scholar
  4. 4.
    J. Dyché, Categorizing Business Intelligence Users, 4 (2007). Retrieved from https://searchbusinessanalytics.techtarget.com/news/2240036691/Categorizing-business-intelligence-users
  5. 5.
    W.W. Eckerson, Performance Dashboards: Measuring, Monitoring, and Managing Your Business, 2nd edn. (Wiley, Hoboken, 2010).  https://doi.org/10.2514/6.2008-3494
  6. 6.
    W.W. Eckerson, Classifying Business Users (2013). Retrieved February 10, 2018, from http://www.b-eye-network.com/blogs/eckerson/archives/2013/09/classifying_bus.php
  7. 7.
    J. Lauer, S. Cameron, J. Nelson, V. Rocca, How to choose the right reporting tools for your instrument control system. Microsoft (2012). Retrieved from https://docs.microsoft.com/en-us/previous-versions/sql/sql-server-2012/jj129615(v=msdn.10)
  8. 8.
    S. Negash, Business intelligence. Commun. Assoc. Inf. Syst. 13, 177–195 (2004).  https://doi.org/10.1002/9781118915240.ch7CrossRefGoogle Scholar
  9. 9.
    E. Turban, R. Sharda, D. Delen, D. King, J.E. Aronson, Business Intelligence: A Managerial Approach, 2nd edn. (Prentice Hall, 2010). Retrieved from https://books.google.com/books?id=IvZ0RAAACAAJ&pgis=1

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Mário Cardoso
    • 1
  • Tiago Guimarães
    • 1
  • Carlos Filipe Portela
    • 1
  • Manuel Filipe Santos
    • 1
    Email author
  1. 1.University of MinhoGuimarãesPortugal

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