Universidade Federal do Rio de Janeiro COPPE

Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia

Instituto de Matemática

 
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Evento: 'Palestra do Prof. Bernhard Mitschang - Augmenting OLAP exploration with dynamic advanced analytics'

Eventos PESC (Palestras, Seminários, etc.)
Palestras, Seminários, etc. do PESC/COPPE/UFRJ.
Data: Tuesday, August 17, 2010 At 14:30
Duração: 2 Horas

Convidamos para a Palestra do Palestra do Prof. Bernhard Mitschang da Universidade de Stuttgart.

Data: 17/08 (3a feira)
Hora: 14:30h
Sala: H-324

Titulo: Augmenting OLAP exploration with dynamic advanced analytics

Online Analytical Processing (OLAP) is a popular technique for explorative data analysis. Usually, a fixed set of dimensions (such as time, place, etc.) is used to explore and analyze various subsets of a given, multi-dimensional data set. These subsets are selected by constraining one or several of the dimensions, for instance, showing sales only in a given year and geographical location. Still, such aggregates are often not enough. Important information can only be discovered by combining several dimensions in a multidimensional analysis. Most existing approaches allow to add new dimensions either statically or dynamically. These approaches support, however, only the creation of global dimensions that are not interactive for the user running the report. Furthermore, they are mostly restricted to data clustering and the resulting dimensions cannot be interactively refined.

In this paper we propose a technique and an architectural solution that is based on an interaction concept for creating OLAP dimensions on subsets of the data dynamically, triggered interactively by the user, based on arbitrary multi-dimensional grouping mechanisms. This approach allows combining the advantages of both, OLAP exploration and interactive multidimensional analysis. We demonstrate the industry-strength of our solution architecture using a setup of IBM® InfoSphere™ Warehouse data mining and Cognos® BI as reporting engine. Use cases and industrial experiences are presented showing how insight derived from data mining can be transparently presented in the reporting front end, and how data mining algorithms can be invoked from the front end, achieving closed-loop integration.

And here a Reference Paper.

Mini CV do Prof. Bernhard

Since 1998, I am professor for Database and Information Systems and head of the department ’Applications of Parallel and Distributed Systems that is part of the Institute of Parallel and Distributed Systems (IPVS) at the Faculty of Computer Science, Electrical Engineering, and Information Technology at the Universität Stuttgart, Stuttgart, Germany. From 1994 to 1998 I held the position of a professor at the Technische Universität München. In 1988 I received the Ph.D. degree (Dr.-Ing.) in Computer Science from the University of Kaiserslautern, and in 1994 I got the venia legendi for practical Computer Science from the University of Kaiserslautern. From 1989 to 1990 I was on leave to IBM Almaden Research Center, San Jose, CA as a visiting scientist, and during Summer semester 2003 I took a sabbatical leave to IBM Deutschland Entwicklung GmbH, Böblingen, Germany, where I started joint work on information services (as part of data-intensive BPEL workflows) and their optimization. During Summer semester 2008 I took another sabbatical leave to IBM Deutschland Research & Development GmbH, Böblingen, Germany, where I started joint work on advanced analytics (covering IBM Intelligent Miner as well as Cognos) and, in addition, I actively supported the joint project on content management as a service.

The research as well as teaching spectrum of my department covers both the broad spectrum of database applications ranging from business applications to engineering systems as well as database kernel and database middleware technologies. My research interests comprise database management systems, including advanced analytics, semantic modelling, query languages, optimizations and parallelism, and application-oriented and service-oriented areas like middleware and component technology, engineering information systems, content management, and knowledge base management systems.


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