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Data Warehouse Fixer: Fixing Inconsistencies in Data Warehouses
2011 30th International Conference of the Chilean Computer Science Society, 2011Dimensions in Data Warehouses (DWs) are set of elements connected by a hierarchical relationship. Usually, dimensions are required to be strict and covering to support summarizations at different levels of granularity. A dimension is strict if all they rollup relations are functions, and is covering if every element in a category is connected with an ...
Alvaro Placencia, Monica Caniupan
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Interoperability in Data Warehouses [PDF]
, 2009 The term refers to the ability of combining the content of two or more heterogeneous data warehouses, for the purpose of cross-analysis. This need emerges in a variety of practical situations. For instance, when different designers of a large company develop their data marts independently, or when different organizations involved in the same project ...
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2013
The previous chapter focused on the analysis of the spatial features of static objects such as stores, cities, or states, where by static we mean that the spatial features of these objects do not change (or change exceptionally) across time. However, there is a wide range of applications that require the analysis of the so-called moving objects, that ...
Vaisman, Alejandro Ariel +1 more
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The previous chapter focused on the analysis of the spatial features of static objects such as stores, cities, or states, where by static we mean that the spatial features of these objects do not change (or change exceptionally) across time. However, there is a wide range of applications that require the analysis of the so-called moving objects, that ...
Vaisman, Alejandro Ariel +1 more
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Fundamentals of Data Warehouses
2000This book presents the first comparative review of the state-of-the-art and the best current practices of data warehouses. It covers source and data integration, multidimensional aggregation, query optimization, metadata management, quality assessment, and design optimization. A conceptual framework is presented by which the architecture and quality of
Jarke Matthias +3 more
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2005
A data warehouse is a large electronic repository of information that is generated and updated in a structured manner by an enterprise over time to aid business intelligence and to support decision making. Data stored in a data warehouse is non-volatile and time variant and is organized by subjects in a manner to support decision making (Inmon, Rudin ...
Beixin (\\"Betsy\\") Lin +2 more
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A data warehouse is a large electronic repository of information that is generated and updated in a structured manner by an enterprise over time to aid business intelligence and to support decision making. Data stored in a data warehouse is non-volatile and time variant and is organized by subjects in a manner to support decision making (Inmon, Rudin ...
Beixin (\\"Betsy\\") Lin +2 more
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2006
The retailing giant Wal-Mart owes its success to the efficient use of information technology in its operations. One of the noteworthy advances made by Wal-Mart is the development of the data warehouse which gives the company a strategic advantage over its competitors.
Lam, A +4 more
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The retailing giant Wal-Mart owes its success to the efficient use of information technology in its operations. One of the noteworthy advances made by Wal-Mart is the development of the data warehouse which gives the company a strategic advantage over its competitors.
Lam, A +4 more
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Data Warehouses Federation as a Single Data Warehouse
2016In this paper author presents an experiment, which shows that it is possible to form a federation of data warehouses that may simulate effectively one, “super” data warehouse. There is no need to create complete ETL tool to load data from source data warehouses into one, dedicated data warehouse.
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International Journal of Data Warehousing and Mining, 2014
This paper presents the idea of deductive data warehouses. Deductive data warehouses rely on deductive databases but instead of a database in the background a data warehouse is used. The authors show how Datalog (as a logic programming language) can be used to perform OLAP analysis on data.
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This paper presents the idea of deductive data warehouses. Deductive data warehouses rely on deductive databases but instead of a database in the background a data warehouse is used. The authors show how Datalog (as a logic programming language) can be used to perform OLAP analysis on data.
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Contextualizing data warehouses with documents
Decision Support Systems, 2008Current data warehouse and OLAP technologies are applied to analyze the structured data that companies store in databases. The context that helps to understand data over time is usually described separately in text-rich documents. This paper proposes to integrate the traditional corporate data warehouse with a document warehouse, resulting in a ...
Pérez Martínez, Juan Manuel +3 more
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A General Model for Data Warehouses
2009Basically, the schema of a data warehouse lies on two kinds of elements: facts and dimensions. Facts are used to memorize measures about situations or events. Dimensions are used to analyse these measures, particularly through aggregation operations (counting, summation, average, etc.).
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