Page 105 - DCAP603_DATAWARE_HOUSING_AND_DATAMINING

Unit 5: Data Warehouse Research – Issues and Research

4. D. Calvanese, G. De Giacomo, M. Lenzerini, D. Nardi, and R. Rosati, Source Integration in notes
Data Warehousing, DEXA’98, 192—197, 1998.
5. G. Zhou, R. Hull, R. King, and J.-C. Franchitti, Supporting Data Integration and Warehousing
Using H2O, IEEE Data Engineering Bulletin, 18:2, 29-40, 1995.
6. Franck Ravat, Olivier Teste, Ronan Tournier, and Gilles Zurfluh, Finding an application-
appropriate model for XML data warehouses, Information Systems, 35:6, 662—687, 2010.
7. J. Gray, H. Schek, M. Stonebraker, and J. Ullman, Lowell Report, 2003.
8. Stefano Rizzi, Open problems in data warehousing: eight years later, DMDW, 2003
(Keynote slides).
9. Eva Kuhn, The Zero-Delay Data Warehouse: Mobilizing Heterogeneous Databases, VLDB,
2003.
10. Rob Weir, Taoxin Peng, and Jon Kerridge, Best Practice for Implementing a Data Warehouse:
A Review for Strategic Alignment, DMDW, 2003.
11. Surajit Chaudhuri, Umeshwar Dayal, and Venkatesh Ganti, Database technology for
decision support systems, IEEE Computer, 48—55, 2001.
12. Surajit Chaudhuri and Umesh Dayal, An Overview of Data Warehousing and OLAP
Technology, ACM SIGMOD Record, 26:1, 1997.

13. M.C. Wu and A.P. Buchmann, Research Issues in Data Warehousing, BTW, 1997.
14. Phillip M. Fernandez and Donovan Schneider, The Ins and Outs (and everything in
between) of Data Warehousing, ACM SIGMOD, 1996 (SIGMOD membership required).

15. Jennifer Widom, Research Problems in Data Warehousing, Int’l Conf. on Information and
Knowledge Management, 1995.
16. P. Raj, Database Design Articles, Overviews, and Resources.
17. Data Warehousing Knowledge Center.

18. Larry Greenfield, Data Warehousing Information Center.
19. R. Kimball, Various articles from Intelligent Enterprise magazine.
20. Data Warehousing Online.

Task Online analytic processing (OLAP) is a simple type of data aggregation
in which the marketer uses an online reporting mechanism to process the information.
Discuss how OLAP used.

5.8 three perspectives of Data Warehouse Metadata

In Figure 5.2 we offer an intuitive view for the categorization of the entities in the process
metamodel. The model has three different perspectives covering distinct aspects of a process:
the conceptual, logical and physical perspective. The categorization is following the separation
of the framework proposed, and fits naturally with the adopted architecture model, since
the perspectives of the process model operate on objects of the respective perspective of the
architecture model. As mentioned there are different ways to view a process: what steps it consists
of (logical perspective), how they are to be performed (physical perspective) and why these steps
exist (conceptual perspective). Thus, we view a data warehouse process from three perspectives:
a central logical part of the model, which captures the basic structure of a process, its physical

LoveLy professionaL university 99