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2013 | 3 | 1 | 40-53

Article title

The Evolution of the Data Warehouse Systems in Recent Years

Content

Title variants

Languages of publication

EN

Abstracts

EN
The article shows the key issues of the data warehouse evolution in recent years. It is divided into six general parts – in the first part a theoretical back-ground was presented to classify the most common used definitions of the data warehouse. In the second and third part the key issues of the data warehouse evolution were presented, such as treating unstructured data. The fourth part of the paper presents the analysis of the data warehouse attributes, whether they are still valid and useful. In the fifth part the paper solutions to mitigate data warehousing weaknesses were presented. Last part shows conclusions.

Year

Volume

3

Issue

1

Pages

40-53

Physical description

Contributors

  • Ph.D., Department of Business Informatics, Faculty of Management, University of Gdańsk, Poland,

References

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  • 3. Bateni M., Golab L., Hajiaghayi M., Karloff H. (2011), Scheduling to Minimize Staleness and Stretch in Real-Time Data Warehouses, [in:] Theory of Computing Systems, Vol. 49, Issue 4, November 2011, p. 757.
  • 4. Chen L., Rahayu W., Taniar D. (2011), Towards Near Real-Time Data Warehousing, [in:] 24th IEEE AINA, p. 1150.
  • 5. Golab L., Johnson T., Shkapenyuk V. (2012), Scalable Scheduling of Updates in Streaming Data Warehouses [in:] IEEE Transactions on Knowledge & Data Engineering, Jun2012, Vol. 24 Issue 6, p. 1092-1093.
  • 6. Hobbs L. (2008), Oracle Database 10g Data Warehousing, Elsevier, p. 4.
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  • 8. Humphries M., Hawkins M.W., Dy M.C. (1999), Data warehousing. Architecture and Implementation, Prentice Hall
  • 9. Inmon W.H. (2005), Bulding the Data Warehouse, Fourth Edition, Wiley Publishing Inc., p. 25, 31-32, 144, 308-310, 429.
  • 10. Inmon W., Strauss D., Neushloss G. (2008), DW 2.0. The Architecture for the Next Generation of Data Warehousing, Morgan Kaufmann, Burlington, p. 9-14.
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  • 12. Januszewski A. (2008), Funkcjonalność informatycznych systemów zarządzania. Tom 2. Systemy Business Intelligence., Wydawnictwo Naukowe PWN SA, p. 21.
  • 13. Khan A.H. (2003), Data warehousing 101. Concepts and implementation., iUniverse, p. 8.
  • 14. Kimball R., Reeves L., Ross M., Thornthwaite W. (1998), The Data Warehouse Lifecycle Toolkit, Wiley Publishing, Inc.
  • 15. Kimball R., Ross. M (2002), The Data Warehouse Lifecycle Toolkit. Second Edition. The Complete Guide to Dimensional Modeling., John Wiley and Sons, p. 7-8.
  • 16. Malinowski E., Zimanyi E. (2009), Advanced Data Warehouse Design. From Conventional to Spatial and Temporal Applications, Springer-Verlag, p. 1-3.
  • 17. Maślankowski J. (2008), Using data warehouse systems in Polish organizations (in Polish), [in:] Infobazy 2008. Systems, applications, services, p. 44-46.
  • 18. Maślankowski J. (2013), Managing methodological changes in the data warehouses (in Polish), [in:] Yearbook of Economics Collegium Analysis 2013 (in printing)
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  • 21. Papastefanatos G., Vassiliadis P., Simitsis A., Vassiliou Y. (2008), Design Metrics for Data Warehouse Evolution, [in:] ER '08 Proceedings of the 27th International Conference on Conceptual Modeling, Springer Berlin Heidelberg, p. 444.
  • 22. Polyzotis N., Skiadopoulos S., Vassiliadis P., Simitsis A., Frantzell N. (2008), Meshing Streaming Updates with Persistent Data in an Active Data Warehouse, [in:] IEEE Transactions on Knowledge & Data Engineering, Jul2008, Vol. 20 Issue 7, p. 976-977.
  • 23. Ponniah P. (2001), Data Warehousing Fundamentals. A Comprehensive Guide for IT Professionals, John Wiley & Sons, Inc., p. 13.
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Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-9c8d717d-93de-426d-aaea-c82c2651b074
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