| the architecture of Datawarehouse [message #92925] |
Tue, 16 April 2002 00:59  |
Mei Tchui
Messages: 4
Registered: April 2002
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Junior Member |
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Can anyone explain to me,
1)the architecture of Oracle 9i Spatial data warehouse and it extensible, scalable and multi-resolution
2)how the database would be organized in terms of table spaces, indexes and views in order to best facilitate the fast loading of data or beside this two what ever info that can help me in my study on
how Oracel 9i Spatial data warehouse can design an Intergrated Spatial Warehouse infrastructure for management, storage, data update, analysis and access of spatial and attribute data.
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| Re: the architecture of Datawarehouse [message #93180 is a reply to message #92925] |
Thu, 19 June 2003 07:02  |
sudheepai
Messages: 1
Registered: June 2003
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Junior Member |
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Can anyone explain to me,
1)the architecture of Oracle 9i Spatial data warehouse and it extensible, scalable and multi-resolution
2)how the database would be organized in terms of table spaces, indexes and views in order to best facilitate the fast loading of data or beside this two what ever info that can help me in my study on
how Oracel 9i Spatial data warehouse can design an Intergrated Spatial Warehouse infrastructure for management, storage, data update, analysis and access of spatial and attribute data.
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| Re: the architecture of Datawarehouse [message #93406 is a reply to message #93265] |
Fri, 03 December 2004 03:53 |
vijay B.R.
Messages: 2
Registered: December 2004
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Junior Member |
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Respected madam,
My name is Vijay, I am studying M.C.A.,I thought of
giving an seminar on Datamining , so I request you to
give me some important information regarding this
topic and help me out.
Kindly do me a favour
Vijay
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| Re: the architecture of Datawarehouse [message #93407 is a reply to message #93180] |
Fri, 03 December 2004 03:55 |
vijay B.R.
Messages: 2
Registered: December 2004
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Junior Member |
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Respected sir,
My name is Vijay, I am studying M.C.A.,I thought of
giving an seminar on Datamining , so I request you to
give me some important information regarding this
topic and help me out.
Kindly do me a favour
vijay
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| Re: the architecture of Datawarehouse [message #158974 is a reply to message #93407] |
Wed, 15 February 2006 05:13 |
krsoujanya
Messages: 8
Registered: July 2005
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Junior Member |
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The above figure shows an overall data warehouse environment. At the extreme left you see the traditional transaction-oriented legacy systems. The data warehouse responsibility starts when you extract data from the legacy systems and enter it into the data staging area.
The data staging area is the complete back-room operation for the data warehouse in which you clean, prune, combine, sort, look up, add keys, remove duplicates, assemble households, archive, and export. The data arriving in the data staging area is frequently dirty, malformed, and in a flat-file format. If you're lucky, the data arrives in perfect third normal form, but that's rare. When you're done cleaning and restructuring the data, you can leave it in flat file form or store it in third normal form. The data staging area is dominated by flat files, simple sorting, and sequential processing. Third normal form relational representations are wonderful, but they're mostly the final result of a lot of hard work done in nonrelational formats.
The key architectural requirement for the data staging area is that it is off limits to the end users. The data staging area is like the back room of a car repair shop. Customers are not allowed in the back room; it isn't safe and the shop doesn't have insurance to cover an injury occurring to a customer in the back room. The mechanics are busy fixing the cars and do not want to be diverted to serving the customers directly. In the same way, the data staging area of the warehouse must be off limits to all forms of end user inquiry. We must not distract ourselves by having to provide availability of data, indexes, aggregations, time series, synchronous integration across subject areas, and especially user-level security.
The presentation area is the complete front-room operation for the data warehouse. As its name implies, the presentation area is on stage and available at all times for end-user inquiry. All forms of end-user inquiry are serviced by the presentation area including ad hoc querying, drilling down, reporting, and data mining. We don't talk about drilling down into an atomic data store located in the back room if that atomic data store is just another name for the data staging area.
The presentation area is broken into subject areas, which are called data marts. Each data mart is organized entirely around effective presenting, which, in my opinion, means dimensional models. Presenting encompasses all inquiry and analysis activities including ad hoc querying, report generation, high-end analysis tools, and data mining. All the dimensional models in all the data marts look somewhat similar, and this suite of dimensional models must share the key dimensions of the enterprise. We call these the conformed dimensions.
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