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A Survey of Managing the Evolution of Data Warehouses

International Journal of Data Warehousing and Mining, 2009
Methods of designing a data warehouse (DW) usually assume that its structure is static. In practice, however, a DW structure changes among others as the result of the evolution of external data sources and changes of the real world represented in a DW ...
R. Wrembel
semanticscholar   +1 more source

The Dimensional Fact Model: A Conceptual Model for Data Warehouses

International Journal of Cooperative Information Systems, 1998
Data warehousing systems enable enterprise managers to acquire and integrate information from heterogeneous sources and to query very large databases efficiently. Building a data warehouse requires adopting design and implementation techniques completely
M. Golfarelli, D. Maio, S. Rizzi
semanticscholar   +1 more source

Contextualizing data warehouses with documents

Decision Support Systems, 2008
Current 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
openaire   +2 more sources

Spatial Data Warehouses

2008
It is estimated that about 80% of the data stored in databases has a spatial or location component. Therefore, the location dimension has been widely used in data warehouse and OLAP systems. However, this dimension is usually represented in an alphanumeric, nonspatial manner (i.e., using solely the place name) since these systems are not able to ...
Esteban Zimányi, Elzbieta Malinowski
openaire   +2 more sources

Data Warehouse Concepts

2014
This chapter introduces the basic concepts of data warehouses. A data warehouse is a particular database targeted toward decision support. It takes data from various operational databases and other data sources and transforms it into new structures that fit better for the task of performing business analysis.
Alejandro Vaisman, Esteban Zimányi
openaire   +2 more sources

The Data Warehouse

2017
The fewer data needed, the better the information. And an overload of information…leads to information blackout.
openaire   +2 more sources

Data Warehouse Patterns

2012
SQL Server Integration Services is an excellent all-purpose ETL tool. Because of its versatility, it is used by DBAs, developers, BI professionals, and even business principals in many different scenarios. Sometimes it’s a dump truck, used for the wholesale movement of enormous amounts of data.
Andy Leonard   +4 more
openaire   +2 more sources

Data Warehouses

2005
Data warehouses (DW) appeared first in industry in the mid 1980s. When their impact on businesses and database practices became clear, a flurry or research took place in academia in the late 1980s and 1990s. However, the concept of DW still remains rooted on its practical origins.
openaire   +1 more source

Designing Secure Data Warehouses

2006
Organizations depend increasingly on information systems, which rely upon databases and data warehouses (DWs), which need increasingly more quality and security. Generally, we have to deal with sensitive information such as the diagnosis made on a patient or even personal beliefs or other sensitive data.
Rodolfo Villarroel   +3 more
openaire   +1 more source

Data Warehouses

Advanced Platform Development with Kubernetes, 2020
C. Johnston
semanticscholar   +1 more source

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