Attribute-Based Fragmentation of XML Data Warehouse

Proceedings of the 8th International Conference on Telecommunications, 2005. ConTEL 2005., 2005

Data warehouse is a database that collects and integrates data from heterogeneous sources in order to support a decision making process. Data exchanged over the Internet and intranets has recently become an important data source, having XML as a standard format for exchange. The possibility of integrating available XML data into data warehouses plays an important role in providing enterprise managers with up-to-date and relevant information about their business domain. We have developed a methodology for data warehouse design from the source XML Schemas and conforming XML documents. As XML data is semi-structured, data warehouse design from XML brings many particular challenges. In this paper the final steps of deriving a conceptual multidimensional scheme are described, followed by the logical design, where a set of tables is created according to the derived conceptual scheme. A prototype tool has been developed to test and verify the proposed methodology.

Information Systems, 2010

Decision support systems help the decision making process with the use of OLAP (On-Line Analytical Processing) and data warehouses. These systems allow the analysis of corporate data. As OLAP and data warehousing evolve, more and more complex data is being used. XML (Extensible Markup Language) is a flexible text format allowing the interchange and the representation of complex data. Finding an appropriate model for an XML data warehouse tends to become complicated as more and more solutions appear. Hence, in this survey paper we present an overview of the different proposals that use XML within data warehousing technology. These proposals range from using XML data sources for regular warehouses to those using full XML warehousing solutions.

Applied Sciences

Data warehousing gives frameworks and means for enterprise administrators to methodically prepare, comprehend, and utilize the data to improve strategic decision-making skills. One of the principal challenges to data warehouse designers is fragmentation. Currently, several fragmentation approaches for data warehouses have been developed since this technique can decrease the OLAP (online analytical processing) query response time and it provides considerable benefits in table loading and maintenance tasks. In this paper, a horizontal fragmentation method, called FTree, that uses decision trees to fragment data warehouses is presented to take advantage of the effectiveness that this technique provides in classification. FTree determines the OLAP queries with major relevance, evaluates the predicates found in the workload, and according to this, builds the decision tree to select the horizontal fragmentation scheme. To verify that the design is correct, the SSB (star schema benchmark) ...

Journal of Decision Systems, 2013

Data Warehouses and OLAP (On Line Analytical Processing) technologies are dedicated to analyzing structured data issued from organizations' OLTP (On Line Transaction Processing) systems. Furthermore, in order to enhance their decision support systems, these organizations need to explore XML (eXtensible Markup Language) documents as an additional and important source of unstructured data. In this context, this paper addresses the warehousing of document-centric XML documents. More specifically, we propose a two-method approach to build Document Warehouse conceptual schemas. The first method is for the unification of XML document structures; it aims to elaborate a global and generic view for a set of XML documents belonging to the same domain. The second method is for designing multidimensional galaxy schemas for Document Warehouses. Les entrepôts de données et les technologies d'analyses en ligne OLAP («On Line Analytical Processing») sont dédiés à l'analyse des données structurées issues des systèmes OLTP («On Line Transaction Processing») des organisations. De plus, ces organisations ont besoin d'explorer des documents XML, comme une importante source additionnelle de données non structurées, à des fins de prise de décisions. Dans ce contexte, cet article s'intéresse à l'entreposage de documents XML orienté-document. Plus particulièrement, nous proposons une approche composées de deux méthodes pour la construction d'un schéma conceptuel d'un Entrepôt de Documents. La première méthode est pour l'unification des structures de documents XML ; elle vise à élaborer une vue globale et générique pour un ensemble de documents XML appartenant à un même domaine. La seconde méthode est pour la modélisation multidimensionnelle en galaxie de schémas d'Entrepôts de Documents.

2013

Data Warehouse (DW) is a collection of subject modelled following different schema (star, snowflake, constellation). It is supplied from different data sources via transactional queries and provides analytical data should be able to handle the diversity of data, query complexity and workload in order to meet the complex decision support queries whose processing time can take several hou uses different optimization techniques: indexing, materialized views, fragmentation and parallelism. The approach suggested in this paper is a optimization is based on the horizontal fragmentation (primary and deriv the task of DW’s administrator, our approach will be accessible via a W horizontal fragmentation schema and scripts needed to implement it. Keywords—Data Warehouse, Web service, Intelligence With the technological advances experienced by Internet, many "conventional" services now use this tool. It is mainly based on Web services: they allow you to share information and provide o...

Faced with the high economic competition, today's enterprises are forced to rely on decision support systems to assist them in the analysis of large data volumes. Traditionally, the analyzed data are mainly issued from the enterprise's operational information system. However, due to the international nature of the competition, enterprises are increasingly pressed to explore other, external data sources, mainly issued from the web. However, despite the convergence of XML as a standard data format on the web, a main difficulty in exploiting these data is the lack of data warehouse design approaches for XML data sources. The few proposed approaches suppose that the designer must first manually identify the XML element that represents the analyzed fact; such a step requires a high expertise and domain knowledge. The main contribution of this paper is to automate this step.

Bulletin of the Technical Committee on, 2001

To achieve good performance of processing queries on huge XML data in cluster machines, data partitioning and placement strategy is one of the key factors. In this paper we propose a multidimensional data structure for maintaining XML data partitions, specifically for holistic twig join processing. Initially, we construct the multidimensional data structure from statistical information on various XML documents and queries execution that have been recorded in the past, such that dimensions of the data structure such as XML tag, query, and XML document can be composed. Also, we outline series of multidimensional analysis operations for generating and maintaining XML data partitions in three basic steps: document clustering, query clustering and partition refinement. Each step yields partitions with their associated costs that are computed by a cost function. As a part of partition refinement, some partitions having considerably high costs resided in overloaded machines are analyzed to select an appropriate multidimensional analysis operation for refinement. Finally, we show the effectiveness of our proposed method with the cost distribution measurement in cluster machines.

Advances in Data Warehousing and Mining, 2009

Data warehousing and OLAP applications must nowadays handle complex data that are not only numerical or symbolic. The XML language is well-suited to logically and physically represent complex data. However, its usage induces new theoretical and practical challenges at the modeling, storage and analysis levels; and a new trend toward XML warehousing has been emerging for a couple of years. Unfortunately, no standard XML data warehouse architecture emerges. In this paper, we propose a unified XML warehouse ...

Data Warehousing and Knowledge Discovery, 2005

Recently, a large number of XML documents are available on the Internet. This trend motivated many researchers to analyze them multi-dimensionally in the same way as relational data. In this paper, we propose a new framework for multidimensional analysis of XML documents, which we call XML-OLAP. We base XML-OLAP on XML warehouses where every fact data as well as dimension data are stored as XML documents. We build XML cubes from XML warehouses. We propose a new multidimensional expression language for XML cubes, which we call XML-MDX. XML-MDX statements target XML cubes and use XQuery expressions to designate the measure data. They specify text mining operators for aggregating text constituting the measure data. We evaluate XML-OLAP by applying it to a U.S. patent XML warehouse. We use XML-MDX queries, which demonstrate that XML-OLAP is effective for multi-dimensionally analyzing the U.S. patents.