SAS/OLAP Server® Software is a powerful, flexible and scalable OLAP solution. It’s hybrid OLAP (HOLAP) architecture provides the flexibility to store data in whatever format is most appropriate based on the characteristics of the data and how the data will be used. This also means, however, that choices must be made as to what is the most appropriate data model for a successful OLAP application...

It has been well recognized that online analytical processing (OLAP) can provide important insights into huge archives of data. While the conventional OLAP model is capable of analyzing relational business data, it often cannot fit many kinds of complex data in emerging applications, such as bio-medical data, time series and semi-structured data. In this paper, we propose GOLAP, a general OLAP ...

The healthcare industry collects huge amounts of data which, unfortunately, are not turned into useful information for effective decision making. Clinical Decision support systems (CDSS) can now use advanced technologies such as On-Line Analytical Processing (OLAP) and Data Mining to deliver advanced capabilities. This paper presents a prototype CDSS using OLAP with Data Mining (OLAP Mining) wh...

Top-k is the most important query type in OLAP, a common data warehouses model. Recently, OLAP was extended to represent data ambiguity, specifically imprecision and uncertainty. However, how to deal with top-k queries in uncertain OLAP still remains an unanswered question. This project introduces a solution for top-k query evaluation in uncertain OLAP including query semantic definition, query...

Top-k is the most important query type in OLAP, the most common data warehouses model. Recently, OLAP was extended to represent data ambiguity, specifically imprecision and uncertainty. However, how to deal with top-k queries in uncertain OLAP still remain an unanswered question. This project introduces a complete solution for top-k query in uncertain OLAP including query semantic definition, q...

This paper discusses the PROMISE (Predicting User Behavior in Multidimensional Information System Environments) approach, that deploys information about characteristic patterns in the user’s multidimensional data access in order to improve caching algorithms of OLAP systems. The paper motivates this approach by presenting results of an analysis of the user behavior in a real-world OLAP environm...

In diesem Paper werden Zeitaspekte in Data Warehouses und deren Auswirkungen auf Online Analytical Processing (OLAP)-Umgebungen behandelt. Nach einer kurzen Darstellung des multidimensionalen Datenmodells und einer grundlegenden OLAP-Architektur werden Veränderungen auf Instanzebene in multidimensionalen Schemen betrachtet. Darüberhinaus wird der Begriff des temporalen OLAP eingeführt: es werde...

Increasingly sophisticated technologies, such as On-Line Analytical Processing (OLAP) and Geospatial Information Systems (GIS), are being leveraged for conducting community health assessments (CHA). Little is known about the usability of OLAP and GIS interfaces with respect to CHA. We conducted an iterative usability evaluation of the Spatial OLAP Visualization and Analysis Tool (SOVAT), a soft...