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Unit 9: Data Warehouse Refreshment – II




          5.   Describe corporate data warehouse.                                               notes
          6.   Distinguish between view maintenance vs data refreshment.

          7.   “Some extraction tools do also the cleaning in the fly while some integrators propagate
               immediately changes until the high level views.” Explain
          8.   If any user desire high freshness for data, this means that each update in a source should
               be mirrored as soon as possible to the views. Discuss
          9.   “Depending on the refreshment scenario, one can choose an appropriate set of event types
               which allows to achieve the correct level of synchronization.” Explain

          10.   What are the  basic uses of data cleaning and data extraction? Explain

          answers: self assessment

          1.   (b)                               2.   (a)
          3.   (d)                               4.   materialized views
          5.   workflow                          6.   refreshment process
          7.   integration step                  8.   improving query performance

          9.   database administrator            10.  remote
          9.10 further readings




           Books      A. K. Jain and R. C. Dubes, Algorithms for Clustering Data, Prentice Hall, 1988.
                      Alex Berson, Data Warehousing Data Mining and OLAP, Tata Mcgraw Hill, 1997

                      Alex  Berson,  Stephen  J.  Smith,  Data  warehousing,  Data  Mining  &  OLAP,  Tata
                      McGraw Hill, Publications, 2004.
                      Alex  Freitas  and  Simon  Lavington,  Mining  Very  Large  Databases  with  Parallel
                      Processing, Kluwer Academic Publishers, 1998.
                      J. Ross Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers,
                      1993.
                      Jiawei Han, Micheline Kamber, Data Mining – Concepts and Techniques, Morgan
                      Kaufmann Publishers, First Edition, 2003.
                      Matthias  Jarke,  Maurizio  Lenzerini,  Yannis  Vassiliou,  Panos  Vassiliadis,
                      Fundamentals of Data Warehouses, Publisher: Springer
                      Michael Berry and Gordon Linoff, Data Mining Techniques (For Marketing, Sales,
                      and Customer Support), John Wiley & Sons, 1997.

                      Michael J. A. Berry, Gordon S Linoff, Data Mining Techniques, Wiley Publishing
                      Inc, Second Edition, 2004.
                      Sam  Anohory,  Dennis  Murray,  Data  Warehousing  in  the  Real  World,  Addison
                      Wesley, First Edition, 2000.
                      Sholom M. Weiss and Nitin Indurkhya, “Predictive Data Mining: A Practical Guide”,
                      Morgan Kaufmann Publishers, 1998.






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