------------------------------------------------------------------------
Speaker:        Panagiotis Kalnis
                Department of Computer Science
                Hong Kong University of Science and Technology

Topic:          "An Introduction to Data Warehousing and On-Line Analytical
                 Processing"

Date:           Wednesday, 28 November 2001

Time:           12:15pm - 1:15pm

Venue:          Room 3501 (via lift nos. 25/26)
                HKUST


ABSTRACT:

Effective decision-making is vital in a global competitive environment,
and business intelligence systems are becoming an essential part of
virtually every organization. The core of such systems is a data
warehouse, which stores historical consolidated data from the
transactional databases and supports complicated ad-hoc queries for
revealing interesting information. The so-called On-Line Analytical
Processing (OLAP) queries usually involve large amounts of data, while
their execution time must be fast enough to allow interactive usage of the
system.

This talk focuses on the basic concepts of data warehousing, analyzing the
necessity of special DBMSs for decision support. We introduce the
multidimensional data model, the notion of the data cube and the
conceptual representation of the warehouse schema. We also present SQL
extensions for supporting OLAP operations, and discuss alternative
physical organizations of the data cube. Finally we overview view
materialization techniques, which constitute the most common optimisation
methods for accelerating OLAP queries.



*******************
Biography:

Panos Kalnis received his Diploma on Computer Engineering in 1997 from the
Computer Engineering and Informatics Dept, University of Patras, Greece.
He has worked on hardware design, web and e-commerce projects and database
systems implementation. He is currently a PhD candidate at the Computer
Science Department, HKUST, working with Dr. Dimitris Papadias. His
research interests include OLAP, Data Warehousing, Peer-to-Peer systems
and Spatial Databases.


                For enquiries, please call  2358 7008
                  **** ALL are Welcome ****
-------------------------------------------------------------------------------