Academic literature on the topic 'Data warehouse'

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Journal articles on the topic "Data warehouse"

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Yang, Peiyuan, Zuwei Shui, Zhou Chen, Baoming Wang, and Han Lei. "Integrated Management of Potential Financial Risks Based on Data Warehouse." Journal of Economic Theory and Business Management 1, no. 2 (2024): 64–70. https://doi.org/10.5281/zenodo.10970487.

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A data warehouse is used to manage an enterprise's vast data sets, providing a storage mechanism to transform data, move data, and present it to end users. This paper introduces the challenges and changes facing the financial industry in the Internet era, and the new needs for data warehouse architecture transformation. The traditional data warehouse architecture has many limitations in the utilization of storage space, computing power and processing of real-time data flow, which is difficult to meet the needs of the rapid development of financial services. Therefore, there is an urgent need f
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Izabela, Rojek. "Data warehouse in production planning." Studies and Materials in Applied Computer Science (ISSN 1689-6300) 11, no. 1 (2020): 8–13. https://doi.org/10.5281/zenodo.4321139.

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The article describes data warehouses in production planning. In particular, the characteristics of production planning and the flow of information and decisions in this planning were discussed. Data warehouses were defined and the architecture of data warehouse systems was presented. As a special case, the possibility of using a data warehouse in production planning in a selected production company was discussed. This article is the first in the introductory cycle to the chosen topic.
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Barahama, A. D., and R. Wardani. "Utilization Extract, Transform, Load For Developing Data Warehouse In Education Using Pentaho Data Integration." Journal of Physics: Conference Series 2111, no. 1 (2021): 012030. http://dx.doi.org/10.1088/1742-6596/2111/1/012030.

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Abstract The utilization of data warehouses in various fields is an absolute necessity. A data warehouse is a database that contains large amounts of data that aims to help organizations, fields, and institutions specifically for decision making. Data warehouses can produce important information in the future. Loading data from various sources and processed through an ETL (Extract, Transform, Load) process that displays data consistently is the basis for creating a data warehouse architecture. The development of a data warehouse in education will provide significant benefits for the progress o
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Vaibhavi, Chide Rajashree Dange* Gauri Darandale Chaitali Dhokane Soham Dhokte Dr. S. D. Mankar. "A Review on Good Warehousing Practices." International Journal of Pharmaceutical Sciences 3, no. 4 (2025): 3014–22. https://doi.org/10.5281/zenodo.15277548.

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Warehouse efficiency is now used by organizations as a strategic weapon or as a center of knowledge.  An efficient warehouse can help a business succeed by promptly meeting consumer needs.  Thus, this study aims to investigate the relationship between warehouse features and warehouse efficiency.  This study examines two aspects of warehouses: their design and how they are used.  This article addresses the vital need to preserve data integrity, accuracy, and dependability in contemporary organizational environments by providing a thorough framework for data quality assurance
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Tan, Jun, and Hai Ming Zhao. "Construction of Data Warehouse Platform in Continual Quality Improvement." Applied Mechanics and Materials 519-520 (February 2014): 13–16. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.13.

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Aiming at improving product quality continually, we proposed an association rules mining system (ARMS) based on idea of PDCA cycling. Data warehouse is very useful for integrating heterogeneous database. Therefore, this paper designed a data warehouse platform as process data exchange module in ARMS. The role of data warehouse platform module is to integrate XML with enterprise process for realizing process data exchange among departments. In design of data warehosue, this paper chooses three-tier data warehouse structure and snowflake schema for indicating the complex relation between process
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Cravero Leal, Ania, Jose Norberto Mazón, and Juan Trujillo. "A business-oriented approach to data warehouse development." Ingeniería e Investigación 33, no. 1 (2013): 59–65. http://dx.doi.org/10.15446/ing.investig.v33n1.37668.

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Several surveys have indicated that many data warehouses fail to meet business objectives or are outright failures. One reason for this is that requirement engineering is typically overlooked in real projects. This paper addresses data warehouse design from a business perspective by highlighting business strategy analysis, alignment between data warehouse objectives and a firm's strategy, goal-oriented information requirements' modelling and how an underlying multidimensional data warehouse model may be derived. A set of guidelines is provided allowing developers to design a data warehouse ali
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Yang, Xiu Fang. "Key Technologies Analysis on Management System Data Warehouse." Applied Mechanics and Materials 644-650 (September 2014): 2925–28. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2925.

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In order to further analyze data warehouse’s application value in teaching management system, this paper first analyzes the disadvantages of previous teaching management system data extraction, illustrates the basic structure of data warehouse system, then discusses the establishment of three kinds of models of data warehouse, finally from the demand perspective of teaching management system, analyzes key technologies such as the design of data warehouse model of teaching management system, the upload of teaching data, data display and data warehouse interfaces.
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Li, Hanzhe, Xiangxiang Wang, Yuan Feng, Yaqian Qi, and Jingxiao Tian. "Integration Methods and Advantages of Machine Learning with Cloud Data Warehouses." International Journal of Computer Science and Information Technology 2, no. 1 (2024): 348–58. http://dx.doi.org/10.62051/ijcsit.v2n1.36.

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A data warehouse is a subject-oriented, integrated, relatively stable collection of data that reflects historical changes and is used to support management decisions. Common tools for building a data warehouse are IBM Cognos and SAP BO. However, both of the above use centralized single-node mode to build data warehouses. This type of data warehouse has poor scalability, and due to the rapid increase in the scale of the Internet, traditional data warehouses can no longer meet the actual needs of use. This paper mainly introduces the integration of cloud data warehouse and machine learning as we
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Spruit, Marco, and Catalina Sacu. "DWCMM: The Data Warehouse Capability Maturity Model." JUCS - Journal of Universal Computer Science 21, no. (11) (2015): 1508–34. https://doi.org/10.3217/jucs-021-11-1508.

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Data Warehouses and Business Intelligence have become popular fields of research in recent years. Unfortunately, in daily practice many Data Warehouse and Business Intelligence solutions still fail to help organizations make better decisions and increase their profitability, due to intransparent complexities and project interdependencies. In addition, emerging application domains such as Mobile Learning & Analytics heavily depend on a well-structured data foundation with a longitudinally prepared architecture. Therefore, this research presents the Data Warehouse Capability Maturity Model (
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Haxhiu, Valdrin. "Decision making based on data analyses using data warehouses." International Journal of Business & Technology 6, no. 3 (2018): 1–6. http://dx.doi.org/10.33107/ijbte.2018.6.3.04.

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Data warehouses are a collection of several databases, whose goal is to help different companies and corporations make important decisions about their activities. These decisions are taken from the analyses that are made to the data within the data warehouse. These data are taken from data that companies and corporations collect on daily basis from their branches that may be located in different cities, regions, states and continents. Data that are entered to data warehouses are historical data and they represent that part of data that is important for making decisions. These data go under a t
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Dissertations / Theses on the topic "Data warehouse"

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Sarkis, Laura Costa. "Data warehouse." Florianópolis, SC, 2001. http://repositorio.ufsc.br/xmlui/handle/123456789/80047.

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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computação.<br>Made available in DSpace on 2012-10-18T09:56:17Z (GMT). No. of bitstreams: 1 227423.pdf: 1120477 bytes, checksum: 7d1d28b65b97dcebee88d4e86dfd4087 (MD5)<br>Este trabalho descreve os conceitos básicos do ambiente do Data Warehouse, abordando em especial o processo de migração de dados. São expostas algumas técnicas e tecnologias mais recentes existentes no mercado com esta finalidade. A partir de um estudo inicial sobre os conceitos de Data Warehouse, delim
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Mathew, Avin D. "Asset management data warehouse data modelling." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/19310/1/Avin_Mathew_Thesis.pdf.

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Data are the lifeblood of an organisation, being employed by virtually all business functions within a firm. Data management, therefore, is a critical process in prolonging the life of a company and determining the success of each of an organisation’s business functions. The last decade and a half has seen data warehousing rising in priority within corporate data management as it provides an effective supporting platform for decision support tools. A cross-sectional survey conducted by this research showed that data warehousing is starting to be used within organisations for their engineering
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Mathew, Avin D. "Asset management data warehouse data modelling." Queensland University of Technology, 2008. http://eprints.qut.edu.au/19310/.

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Data are the lifeblood of an organisation, being employed by virtually all business functions within a firm. Data management, therefore, is a critical process in prolonging the life of a company and determining the success of each of an organisation’s business functions. The last decade and a half has seen data warehousing rising in priority within corporate data management as it provides an effective supporting platform for decision support tools. A cross-sectional survey conducted by this research showed that data warehousing is starting to be used within organisations for their engineering
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Sharathkumar, Sudhindra. "An Automated Data Warehouse." ScholarWorks@UNO, 2003. http://scholarworks.uno.edu/td/36.

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An increasing number of organizations are implementing data warehouses to strengthen their decision support systems. This comes with the challenges of the population and the periodic update of data warehouses. In this thesis, we present a tool that provides users with features to create a warehouse database and transform structures of the source database into structures for the warehouse database. It is highly interactive, easy to use, and hides the underlying complexity of manual SQL code generation from its users. Attributes from source tables can be mapped into new attributes in the w
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Qian, Yi. "Financial aid data warehouse /." Connect to title online, 2008. http://minds.wisconsin.edu/handle/1793/34216.

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Hinrichs, Holger. "Datenqualitätsmanagement in Data-warehouse-Systemen." [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=964461552.

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Mazzola, Irany Salgado. "Projeto de data warehouse dimensional." Florianópolis, SC, 2002. http://repositorio.ufsc.br/xmlui/handle/123456789/83465.

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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computação.<br>Made available in DSpace on 2012-10-20T00:16:39Z (GMT). No. of bitstreams: 1 184713.pdf: 304047 bytes, checksum: dd66fd6662914e352a967197f0859c9a (MD5)<br>O objetivo do trabalho é propor um projeto de modelagem de um Data Warehouse Dimensional para uma empresa do ramo varejista, com diversas áreas cujas informações alimentam o sistema de informações apoiado no DW. Um Data Warehouse é uma tecnologia de articulação inacabada, que estrutura e formaliza as inf
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Kanna, Rajesh. "Managing XML data in a relational warehouse on query translation, warehouse maintenance, and data staleness /." [Gainesville, Fla.] : University of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/anp4011/Thesis.PDF.

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Thesis (M.S.)--University of Florida, 2001.<br>Title from first page of PDF file. Document formatted into pages; contains x, 75 p.; also contains graphics. Vita. Includes bibliographical references (p. 71-74).
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Redgert, Rebecca. "Evaluating Data Quality in a Data Warehouse Environment." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208766.

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The amount of data accumulated by organizations have grown significantly during the last couple of years, increasing the importance of data quality. Ensuring data quality for large amounts of data is a complicated task, but crucial to subsequent analysis. This study investigates how to maintain and improve data quality in a data warehouse. A case study of the errors in a data warehouse was conducted at the Swedish company Kaplan, and resulted in guiding principles on how to improve the data quality. The investigation was done by manually comparing data from the source systems to the data integ
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Öhman, Mikael. "a Data-Warehouse Solution for OMS Data Management." Thesis, Umeå universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-80688.

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A database system for storing and querying data of a dynamic schema has been developed based on the kdb+ database management system and the q programming language for use in a financial setting of order and execution services. Some basic assumptions of mandatory fields of the data to be stored are made including that the data are time-series based.A dynamic schema enables an Order-Management System (OMS) to store information not suitable or usable when stored in log files or traditional databases. Log files are linear, cannot be queried effectively and are not suitable for the volumes produced
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Books on the topic "Data warehouse"

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Vaisman, Alejandro, and Esteban Zimányi. Data Warehouse Systems. Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-65167-4.

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Schütte, Reinhard, Thomas Rotthowe, and Roland Holten, eds. Data Warehouse Managementhandbuch. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56847-3.

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von Maur, Eitel, and Robert Winter, eds. Data Warehouse Management. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55477-3.

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Vaisman, Alejandro, and Esteban Zimányi. Data Warehouse Systems. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54655-6.

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H, Inmon William, ed. Data warehouse performance. Wiley, 1999.

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H, Inmon William, ed. Data warehouse performance. John Wiley, 1998.

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Kimball, Ralph. The data warehouse toolkit: Practical techniques for building dimensional data warehouses. John Wiley & Sons, 1996.

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Mucksch, Harry, and Wolfgang Behme, eds. Das Data-Warehouse-Konzept. Gabler Verlag, 1996. http://dx.doi.org/10.1007/978-3-663-13657-6.

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Wirtz, Katharina. Der Data-Warehouse-Rahmenplan. Deutscher Universitätsverlag, 2002. http://dx.doi.org/10.1007/978-3-322-81419-7.

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Behme, Wolfgang, and Harry Mucksch, eds. Data Warehouse-gestützte Anwendungen. Gabler Verlag, 2001. http://dx.doi.org/10.1007/978-3-322-90222-1.

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Book chapters on the topic "Data warehouse"

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Kaiser, Bernd-Ulrich. "Data Warehouse." In Unternehmensinformation mit SAP®-EIS. Vieweg+Teubner Verlag, 1998. http://dx.doi.org/10.1007/978-3-322-94272-2_3.

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Kaiser, Bernd-Ulrich, and Stephen Fedtke. "Data Warehouse." In Unternehmensinformation mit SAP®-EIS. Vieweg+Teubner Verlag, 1999. http://dx.doi.org/10.1007/978-3-663-07821-0_3.

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Song, Il-Yeol. "Data Warehouse." In Encyclopedia of Database Systems. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_882-3.

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Hopfmann, Lienhard. "Data Warehouse." In Power Tools. Gabler Verlag, 2001. http://dx.doi.org/10.1007/978-3-322-84461-3_17.

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Colhoun, O. "Data Warehouse." In Springer Reference Medizin. Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-48986-4_826.

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Colhoun, O. "Data Warehouse." In Lexikon der Medizinischen Laboratoriumsdiagnostik. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-49054-9_826-1.

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Song, Il-Yeol. "Data Warehouse." In Encyclopedia of Database Systems. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_882.

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Herden, Olaf. "Data Warehouse." In Taschenbuch Datenbanken. Carl Hanser Verlag GmbH & Co. KG, 2015. http://dx.doi.org/10.3139/9783446440265.014.

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Cordts, Sönke, Gerold Blakowski, and Gerhard Brosius. "Data Warehouse." In Datenbanken für Wirtschaftsinformatiker. Vieweg+Teubner, 2011. http://dx.doi.org/10.1007/978-3-8348-8192-2_19.

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Song, Il-Yeol. "Data Warehouse." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_882.

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Conference papers on the topic "Data warehouse"

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Caniupan, M., and A. Placencia. "Data Warehouse Fixer: Fixing Inconsistencies in Data Warehouses." In 2011 30th International Conference of the Chilean Computer Science Society (SCCC 2011). IEEE, 2011. http://dx.doi.org/10.1109/sccc.2011.5.

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Moulai, Hadjer, and Habiba Drias. "From Data Warehouse to Information Warehouse." In the International Conference. ACM Press, 2018. http://dx.doi.org/10.1145/3230905.3230914.

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ElGamal, Neveen, Ali ElBastawissy, and Galal Galal-Edeen. "Data warehouse testing." In the Joint EDBT/ICDT 2013 Workshops. ACM Press, 2013. http://dx.doi.org/10.1145/2457317.2457319.

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Yi, Xun, Russell Paulet, Elisa Bertino, and Guandong Xu. "Private data warehouse queries." In the 18th ACM symposium. ACM Press, 2013. http://dx.doi.org/10.1145/2462410.2462418.

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Arfaoui, Nouha, and Jalel Akaichi. "Vehicle trajectory data warehouse." In ICC '17: Second International Conference on Internet of Things, Data and Cloud Computing. ACM, 2017. http://dx.doi.org/10.1145/3018896.3056790.

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Blazic, G., P. Poscic, and D. Jaksic. "Data warehouse architecture classification." In 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE, 2017. http://dx.doi.org/10.23919/mipro.2017.7973657.

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Turki, Ines Zouari, Faiza Ghozzi Jedidi, and Rafik Bouaziz. "Multiversion data warehouse constraints." In the ACM 13th international workshop. ACM Press, 2010. http://dx.doi.org/10.1145/1871940.1871945.

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Ravat, Franck, Olivier Teste, and Giles Zurfluh. "Towards data warehouse design." In the eighth international conference. ACM Press, 1999. http://dx.doi.org/10.1145/319950.320028.

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Karima, Tekaya, Abdellaziz Abdelatif, and Ounalli Habib. "Data Warehouse Decentralization Strategy." In 2010 IEEE 7th International Conference on e-Business Engineering (ICEBE). IEEE, 2010. http://dx.doi.org/10.1109/icebe.2010.109.

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Shuigeng Zhou, Aoying Zhou, Xiaopeng Tao, and Yunfa Hu. "Hierarchically distributed data warehouse." In Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region. IEEE, 2000. http://dx.doi.org/10.1109/hpc.2000.843558.

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Reports on the topic "Data warehouse"

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Kramer, Mitchell. Data Warehouse Databases. Patricia Seybold Group, 2003. http://dx.doi.org/10.1571/fw3-6-03cc.

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Kramer, Mitchell. DB2 Data Warehouse Enterprise Edition. Patricia Seybold Group, 2003. http://dx.doi.org/10.1571/pr9-11-03cc.

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Lee, Sangkeun, Supriya Chinthavali, Mallikarjun Shankar, Claire Zeng, and Stephen Hendrickson. Energy Finance Data Warehouse Manual. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1342691.

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Kramer, Mitchell. PSGroup Bull's-Eye: Data Warehouse Databases. Patricia Seybold Group, 2003. http://dx.doi.org/10.1571/psgb11-20-03cc.

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Kramer, Mitchell. PSGroup Bull's-Eye: Data Warehouse Databases. Patricia Seybold Group, 2003. http://dx.doi.org/10.1571/psgb11-26-03cc.

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Kramer, Mitchell. PSGroup Bull's-Eye: Data Warehouse Databases. Patricia Seybold Group, 2003. http://dx.doi.org/10.1571/psgb12-4-03cc.

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Reddy, Prameela V., and Charles G. Schroeder. Data Warehouse Architecture for Army Installations. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada371882.

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Kramer, Mitchell. Data Warehouse Database Feature Comparison Matrix. Patricia Seybold Group, 2003. http://dx.doi.org/10.1571/cm11-13-03cc.

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Ulmer, Craig, Nathan Fabian, Todd Kordenbrock, Shyamali Mukherjee, and Ron Oldfield. ATDM Data Management FY2015: Data Warehouse Progress Report. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1770714.

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Zhang, Xin, and Elke A. Rundensteiner. Data Warehouse Maintenance Under Concurrent Schema and Data Updates. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada386236.

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