Title:   Survey on OLAP
Speaker: Kian Win Ong (UCSD), Nicola Onose (UCSD)

Abstract:

Decision support represents a field with many industrial applications
and with characteristics that were not addressed by classical on-line
transaction processing (OLTP) supported by traditional database systems.
On-line analytical processing (OLAP) is one of the key elements in this
new scenario which requires running complex queries with
multidimensional aggregation over very large databases created by
consolidating historical data.

The talk surveys the field by presenting several classical papers from
the mid-90s. We start by introducing the data cube, a standard
conceptual model for OLAP and then move gradually towards optimization
techniques proposed for reducing the space and time costs for
implementing the operations on this structure.