Cargando…

Advanced Data Warehouse Design From Conventional to Spatial and Temporal Applications /

A data warehouse stores large volumes of historical data required for analytical purposes. This data is extracted from operational databases; transformed into a coherent whole using a multidimensional model that includes measures, dimensions, and hierarchies; and loaded into a data warehouse during...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Malinowski, Elzbieta (Autor), Zimányi, Esteban (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Data-Centric Systems and Applications,
Temas:
Acceso en línea:Texto Completo

MARC

LEADER 00000nam a22000005i 4500
001 978-3-540-74405-4
003 DE-He213
005 20220117114814.0
007 cr nn 008mamaa
008 100301s2008 gw | s |||| 0|eng d
020 |a 9783540744054  |9 978-3-540-74405-4 
024 7 |a 10.1007/978-3-540-74405-4  |2 doi 
050 4 |a QA76.9.D35 
050 4 |a Q350-390 
072 7 |a UMB  |2 bicssc 
072 7 |a GPF  |2 bicssc 
072 7 |a COM031000  |2 bisacsh 
072 7 |a UMB  |2 thema 
072 7 |a GPF  |2 thema 
082 0 4 |a 005.73  |2 23 
082 0 4 |a 003.54  |2 23 
100 1 |a Malinowski, Elzbieta.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Advanced Data Warehouse Design  |h [electronic resource] :  |b From Conventional to Spatial and Temporal Applications /  |c by Elzbieta Malinowski, Esteban Zimányi. 
250 |a 1st ed. 2008. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2008. 
300 |a XXI, 435 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Data-Centric Systems and Applications,  |x 2197-974X 
505 0 |a to Databases and Data Warehouses -- Conventional Data Warehouses -- Spatial Data Warehouses -- Temporal Data Warehouses -- Designing Conventional Data Warehouses -- Designing Spatial and Temporal Data Warehouses -- Conclusions and Future Work. 
520 |a A data warehouse stores large volumes of historical data required for analytical purposes. This data is extracted from operational databases; transformed into a coherent whole using a multidimensional model that includes measures, dimensions, and hierarchies; and loaded into a data warehouse during the extraction-transformation-loading (ETL) process. Malinowski and Zimányi explain in detail conventional data warehouse design, covering in particular complex hierarchy modeling. Additionally, they address two innovative domains recently introduced to extend the capabilities of data warehouse systems, namely the management of spatial and temporal information. Their presentation covers different phases of the design process, such as requirements specification, conceptual, logical, and physical design. They include three different approaches for requirements specification depending on whether users, operational data sources, or both are the driving force in the requirements gathering process, and they show how each approach leads to the creation of a conceptual multidimensional model. Throughout the book the concepts are illustrated using many real-world examples and completed by sample implementations for Microsoft's Analysis Services 2005 and Oracle 10g with the OLAP and the Spatial extensions. For researchers this book serves as an introduction to the state of the art on data warehouse design, with many references to more detailed sources. Providing a clear and a concise presentation of the major concepts and results of data warehouse design, it can also be used as the basis of a graduate or advanced undergraduate course. The book may help experienced data warehouse designers to enlarge their analysis possibilities by incorporating spatial and temporal information. Finally, experts in spatial databases or in geographical information systems could benefit from the data warehouse vision for building innovative spatial analytical applications. 
650 0 |a Data structures (Computer science). 
650 0 |a Information theory. 
650 0 |a Database management. 
650 0 |a Geographic information systems. 
650 0 |a Business information services. 
650 0 |a Environmental monitoring. 
650 0 |a Earth sciences. 
650 1 4 |a Data Structures and Information Theory. 
650 2 4 |a Database Management. 
650 2 4 |a Geographical Information System. 
650 2 4 |a IT in Business. 
650 2 4 |a Environmental Monitoring. 
650 2 4 |a Earth Sciences. 
700 1 |a Zimányi, Esteban.  |e author.  |0 (orcid)0000-0003-1843-5099  |1 https://orcid.org/0000-0003-1843-5099  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783540842668 
776 0 8 |i Printed edition:  |z 9783642093838 
776 0 8 |i Printed edition:  |z 9783540744047 
830 0 |a Data-Centric Systems and Applications,  |x 2197-974X 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-540-74405-4  |z Texto Completo 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710)