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A Survey on Temporal Data Warehousing

International Journal of Data Warehousing and Mining, 2009
Data warehouses are information repositories specialized in supporting decision making. Since the decisional process typically requires an analysis of historical trends, time and its management acquire a huge importance. In this paper we consider the variety of issues, often grouped under term temporal data warehousing, implied by the need for ...
GOLFARELLI, MATTEO, RIZZI, STEFANO
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Data stream warehousing

2014 IEEE 30th International Conference on Data Engineering, 2013
Data stream warehousing is a data management technology designed to simultaneously handle big-data and fast-data. Conceptually, a data stream warehouse can be thought of as a data warehouse system that is updated in nearly-real time rather than during downtimes, or as a data stream management system that stores a very long history. In this tutorial, we
Lukasz Golab, Theodore Johnson
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Data Warehousing and OLAP Technology (Data warehousing)

International Journal of Engineering Trends and Technology, 2017
Priyanka Jaroli, Palak Masson
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Data Warehousing [PDF]

, 2014
Data ...
Elvis C. Foster, Shripad V. Godbole
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Persistence in Data Warehousing

2012 Sixth International Conference on Research Challenges in Information Science (RCIS), 2012
Persistence of redundant data in Data Warehouses is often simply justified with an achievement of better performance when accessing data for analysis and reporting. However, there are other reasons to store data persistently, which are often not recognized when designing Data Warehouses.
Thorsten Winsemann, Veit Köppen
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Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing

SIGMOD Conference, 2019
Apache Hive is an open-source relational database system for analytic big-data workloads. In this paper we describe the key innovations on the journey from batch tool to fully fledged enterprise data warehousing system.
Jesús Camacho-Rodríguez, Ashutosh Chauhan, Alan Gates, E. Koifman, Owen O'Malley, Vineet Garg, Zoltan Haindrich, S. Shelukhin, Prasanth Jayachandran, S. Seth, D. Jaiswal, Slim Bouguerra, Nishant Bangarwa, Sankar Hariappan, Anish Agarwal, Jason Dere, Daniel Dai, Thejas Nair, Nita Dembla, Gopal Vijayaraghavan, Günther Hagleitner   +20 more
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Preparing complex data for warehousing

The 3rd ACS/IEEE International Conference onComputer Systems and Applications, 2005., 2005
Summary form only given. In order to prepare complex data for relevant analysis, a data warehousing-based approach is needed. However, a good multidimensional modeling requires efficient preparation of data starting with a data integration phase. We present in this paper two principal steps of the complex data warehousing process.
Tanasescu, Adrian, Boussaid, Omar, Bentayeb, Fadila   +2 more
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Data warehousing techniques

Proceedings of the International Conference & Workshop on Emerging Trends in Technology - ICWET '11, 2011
DW is an information delivery system. It is a repository of integrated information, available for queries and analysis. Data & information are extracted from heterogeneous sources as they are generated. This makes it much easier & more efficient to run queries over data that originally came from different sources.
K. Kiran Dubey, Devidas Kalwale
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Green warehousing, logistics optimization, social values and ethics and economic performance: the role of supply chain sustainability

, 2020
This study primarily explores the influence of green warehousing, logistics optimization and social values and ethics on supply chain sustainability and economic performance.
Yaw Agyabeng‐Mensah, Esther Ahenkorah, Ebenezer Afum, Essel Dacosta, Zhongxing Tian   +4 more
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