P. Forbrig and H. Günther (Eds.): BIR 2010, LNBIP 64, pp. 188–202, 2010. © Springer-Verlag Berlin Heidelberg 2010 OLAP Personalization with User-Describing Profiles Natalija Kozmina and Laila Niedrite Faculty of Computing, University of Latvia, Riga LV-1586, Latvia {natalija.kozmina,laila.niedrite}@lu.lv Abstract. In this paper we have highlighted five existing approaches for introducing personalization in OLAP: preference constructors, dynamic personalization, visual OLAP, recommendations with user session analysis and recommendations with user profile analysis and have analyzed research papers within these directions. We have pointed out applicability of personalization to OLAP schema elements in these approaches. The comparative analysis has been made in order to highlight a certain personalization approach. A new method has been proposed, which provides exhaustive description of interaction between user and data warehouse, using the concept of Zachman Framework [1, 2], according to which a set of user-describing profiles (user, preference, temporal, spatial, preferential and recommendational) have been developed. Methods of profile data gathering and processing are described in this paper. Keywords: OLAP personalization, user preferences, profiles. 1 Introduction and Related Work The OLAP applications are built to perform analytical tasks within large amount of multidimensional data. During working sessions with OLAP applications the working patterns can be various. Due to the large volumes of data the typical OLAP queries performed via OLAP operations by users may return too much information that sometimes makes further data exploration burdening or even impossible. A query personalization method that takes user likes and dislikes into consideration exists in traditional databases [3]. Similar ideas seem attractive also for research in the data warehousing field and the topicality of this issue is demonstrated in the recent works of many authors on data warehouse personalization. There are various aspects of data warehouse personalization. Data warehouse can be personalized at the schema level [4]. As a result, a data warehouse user is able to work with a personalized OLAP schema Users may express their preferences on OLAP queries [5]. In this case, the problem of performing time-consuming OLAP operations to find the necessary data can be significantly improved. One of the methods of personalizing OLAP systems is to provide query recommendations to data warehouse users. OLAP recommendation techniques are proposed in [6] and [7]. In [6] former sessions of the same data warehouse user are being investigated. User profiles that contain user preferences are taken into consideration in [7], while generating query recommendations.