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...

On-line analytical processing (OLAP) systems deal with analytical tasks in businesses. As these tasks do not depend on the latest updates by transactions, it is assumed that the data used in OLAP systems are kept in a data warehouse, which separates the input coming from operational databases from the output going to dialogue interfaces for OLAP. In this article we present a 3-tier architecture...

Nenad Jukic 1 , Boris Jukic 2 , and Mary Malliaris 1 School of Business Administration, Loyola University Chicago, Chicago, IL, USA School of Business, Clarkson University, Potsdam, NY, USA _____________________________________________________________________________________ Online Analytical Processing (OLAP) refers to the general activity of querying and presenting text and number data from d...

On-Line Analytical Processing (OLAP) is a trend in database technology, based on the multidimensional view of data. Numerous applications and development environments exist, offering OLAP analysis to developers, analysts and end users. Further more, mobile devices find their way into almost all aspects of every day life, ranging from cellular phones with advanced capabilities (smart phones) for...

The ever-changing data requirements of today’s dynamic businesses are not handled well by current OnLine Analytical Processing (OLAP) systems. Physical integration of unexpected data into OLAP systems is a long and time-consuming process, making logical integration, or federation, the better choice in many cases. The increasing use of XML, e.g. in business-to-business (B2B) applications, sugges...

We present the logical “OLAP-XML Federation System” that enables the external data available in XML format to be used as virtual dimensions. Unlike the complex and time-consuming physical integration of OLAP and external data in current OLAP systems, our system makes OLAP queries referencing fast-changing external data possible. This demo shows the uses of XML data for selection and grouping an...

BACKGROUND Prognostic counseling in multiple sclerosis (MS) is difficult because of the high variability of disease progression. Simultaneously, patients and physicians are increasingly confronted with making treatment decisions at an early stage, which requires taking individual prognoses into account to strike a good balance between benefits and harms of treatments. It is therefore important ...

Data warehouse and OLAP are core aspects of business intelligence environments, since the former store integrated and time-variant data, while the latter enables multidimensional queries, visualization and analysis. The bitmap join index has been recognized as an efficient mechanism to speed up queries over data warehouses. However, existing OLAP tools does not use strictly this index to improv...

Multidimensional databases are a great asset for decision making. Their users express complex OLAP (On-Line Analytical Processing) queries, often returning huge volumes of facts, sometimes providing little or no information. Furthermore, due to the huge volume of historical data stored in DWs, the OLAP applications may return a big amount of irrelevant information that could make the data explo...