THE TECHNIQUE OF ADAPTIVE CONTROL IN DESIGN AND DEVELOPMENT PROCESS OF SPECIALIZED DATA WAREHOUSE


如何引用文章

全文:

详细

The technique of adaptive control in process of designing and developing data warehouses is proposed. The technique provides original formalization of the design and development of the data warehouse model and it takes into account the operating conditions and specific information about data domain. The description of the design and development of specialized data warehouse using the management model in the notation eEPC ARIS-methodology is executed.

参考

  1. Gupta H., Afrati F. N., Kolaitis P. G. Selection of views to materialize in a data warehouse // Proc. of the 6th Intern. Conf. on Database theory // Eds. Lecture Notes In Computer Science. London: Springer-Verlag, 1997. P. 98-112.
  2. Бадмаева К. В. Алгоритм оценки релевантности представлений для материализации в специализированном хранилище данных // Вестник СибГАУ. 2009. Вып. 1(22). В 2 ч. Ч. 2. С. 60-64.
  3. Badmaeva K. The performance of specialized data warehouses increasing // Proc. of the IASTED Intern. Conf. on Automaton, Control and Information Technology. Novosibirsk, 2010. P. 206-210. 4.
  4. Моделирование бизнеса. Методология ARIS / М. Каменова, А. Громов, М. Ферапонтов, А. Шматалюк. М.: Метатехнология, 2001.
  5. Спирли Э. Корпоративные хранилища данных. Планирование, разработка, реализация. М.: Вильямс, 2001.
  6. Kimball R., Ross M. The data warehouse toolkit: the complete guide to dimensional modeling. N. Y.: John Wiley & Sons, Inc., 2002.
  7. Inmon W. H. Building the data warehouse. N. Y.: John Willey & Sons, 1992.
  8. Buzydlowski J. W., Song I., Hassell L. A framework for object-oriented on-line analytic processing // Proc. of the 1 st ACM Intern. Workshop on Data Warehousing and OLAP. N. Y. 1998. P. 10-15.
  9. Golfarelli M., Rizzi S. A methodological framework for data warehouse design // Proc. of the 1st Intern. Workshop on Data Warehousing and OLAP. Maryland, 1998. P. 3-9. 10.
  10. Extending the E/R model for the multidimensional paradigm / C. Sapia, M. Blaschka, G. Hëofling, B. Dinter // Proc. ER Workshop on Data Warehousing and Data Mining. Singapore, 1998. P. 105-116.
  11. Tryfona N., Busborg F., Christiansen J. StarER: A conceptual model for data warehouse design // Proc. of the ACM 2nd Intern. Workshop on Data Warehousing and OLAP/ Kansas City. 1999. P. 3-8.
  12. Kamble A. S. A conceptual model for multidimensional data // Proc. of the Fifth on Asia-Pacific Conf. on Conceptual Modelling; Australian Computer Society, Darlinghurst, Australia, 2008. Vol. 79. P. 29-38.
  13. Baralis E., Paraboschi S., Teniente E. Materialized views selection in a multidimensional database // Proc. of the 23rd Intern. Conf. on Very Large Data Bases, Eds. Very Large Data Bases. San Francisco: Morgan Kaufmann Publishers, 1997. P. 156-165.
  14. Harinarayan V., Rajaraman A., Ullman J. D. Implementing data cubes efficiently // Proc. of the 1996 ACM SIGMOD Intern. Conf. on Management of Data. Quebec, 1996. P. 205-216. 15.
  15. Efficient approaches for materialized views selection in a data warehouse / M. Hung, M. Huang, D. Yang, N. Hsueh // Information Sciences. 2007. № 177. P. 1333-1348.

补充文件

附件文件
动作
1. JATS XML

版权所有 © Badmaeva K.V., Badmaeva K.V., 2010

Creative Commons License
此作品已接受知识共享署名 4.0国际许可协议的许可