Search results for "online analytical processing"
showing 10 items of 13 documents
Towards Introducing User Preferences in OLAP Reporting Tool
2012
This paper presents an OLAP reporting tool and an approach for determining and processing user OLAP preferences, which are useful for generating recommendations on potentially interesting reports. We discuss the metadata layers of the reporting tool including our proposed OLAP preferences metamodel, which supports various scenarios of formulating preferences of two different types: schema-specific and report-specific. The process of semantic metadata usage at the stage of formulating user preferences is also considered. The methods for processing schema-specific and report-specific OLAP preferences are outlined.
The Hierarchical Agglomerative Clustering with Gower index: a methodology for automatic design of OLAP cube in ecological data processing context
2015
In Press, Corrected Proof; International audience; The OLAP systems can be an improvement for ecological studies. In fact, ecology studies, follows and analyzes phenomenon across space and time and according to several parameters. OLAP systems can provide to ecologists browsing in a large dataset. One focus of the current research on OLAP system is the automatic design of OLAP cubes and of data warehouse schemas. This kind of works makes accessible OLAP technology to non information technology experts. But to be efficient, the automatic OLAP building must take into account various cases. Moreover the OLAP technology is based on the concept of hierarchy. Thereby the hierarchical clustering m…
Research Directions of OLAP Personalizaton
2011
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 provided an evaluation in order to point out (i) personalization options, described in these approaches, and its applicability to OLAP schema elements, aggregate functions, OLAP operations, (ii) the type of constraints (hard, soft or other), used in each approach, (iii) the methods for obtaining user preferences and collecting user information. The goal of our paper is to syst…
Opportunities for the Use of Business Data Analysis Technologies
2016
Abstract The paper analyses the business data analysis technologies, provides their classification and considers relevant terminology. The feasibility of business data analysis technologies handling big data sources is overviewed. The paper shows the results of examination of the online big data source analytics technologies, data mining and predictive modelling technologies and their trends.
Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering
2015
20 pages; International audience; Data warehouses (DW) and OLAP systems are business intelligence technologies allowing the on-line analysis of huge volume of data according to users' needs. The success of DW projects essentially depends on the design phase where functional requirements meet data sources (mixed design methodology) (Phipps and Davis, 2002). However, when dealing with complex applications existing design methodologies seem inefficient since decision-makers define functional requirements that cannot be deduced from data sources (data driven approach) and/or they have not sufficient application domain knowledge (user driven approach) (Sautot et al., 2014b). Therefore, in this p…
Change Discovery in Heterogeneous Data Sources of a Data Warehouse
2020
Data warehouses have been used to analyze data stored in relational databases for several decades. However, over time, data that are employed in the decision-making process have become so enormous and heterogeneous that traditional data warehousing solutions have become unusable. Therefore, new big data technologies have emerged to deal with large volumes of data. The problem of structural evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. In this paper, we propose an approach to change discovery in data sources of a data warehouse utilized to analyze big data. Our solution incorporates an architecture that allows t…
Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology
2017
[Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]MOTIVE; International audience; Designing and building a Data Warehouse (DW), and associated OLAP cubes, are long processes, during which decision-maker requirements play an important role. But decision-makers are not OLAP experts and can find it difficult to deal with the concepts behind DW and OLAP. To support DW design in this context, we propose: (i) a new rapid prototyping methodology, integrating two different DM algorithms, to define dimension hierarchies according to decision-maker knowledge; (ii) a complete UML Profile, to define a DW schema that integrates both the DM algorithms; (iii) a mapping process to transform multidimensional …
Using OLAP Data Cubes in Business Intelligence
2016
Abstract The purpose of this paper is to demonstrate that it is possible to develop business intelligence projects in big and medium-size organizations, only with Microsoft products, used in accordance with standard OLAP cube technology, and presented possible alternatives, in relation with the requested functions.
On Metadata Support for Integrating Evolving Heterogeneous Data Sources
2019
With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and tran…
An empirical study of recommendations in OLAP reporting tool
2015
This paper presents the results of the experimental study that was performed in laboratory settings in the context of the OLAP reporting tool developed and put to operation at the University. The study was targeted to explore which of the modes for generating recommendations in the OLAP reporting tool has a deeper impact on users (i.e. produces more accurate recommendations). Each of the modes of the recommendation component â report structure, user activity, and semantic â employs a separate content-based method that takes advantage of OLAP schema metadata and aggregate functions. Gained data are assessed (i) quantitatively by means of the precision/recall and other metrics from the lo…