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Oracle Data Warehouse & BI

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 Oracle Data Warehouse

 

 

A data warehouse (DW) is MAINLY a database used for reporting.

 

Because of this purpose the DW is structured differently as an OLTP (transactional) database.

 

A data warehouse maintains its functions in three layers: staging, integration, and access.

         Staging layer is used to store raw data (for analysis and support);

         The integration layer is used to integrate data and to have a level of abstraction from users;

         The access layer is for getting data out for users.

 


A data warehouse is a consolidated view of your enterprise data, optimized for reporting and analysis.

 

Basically it is an aggregated, sometimes summarized copy of transaction and non-transaction data specifically structured for dynamic queries and analytics. In data warehousing, data and information are extracted from heterogeneous production data sources (different databases, different database technologies) as they are generated, or in periodic stages, making it simpler and more efficient to run queries over data that originally came from different sources. Data is turned into high-quality information to meet all enterprise reporting requirements for all levels of users. Interactive content can be delivered to anyone in the extended enterprise – customers, partners, employees, managers, and executives – anytime, anywhere.

 

Conclusion:

A DW (Data Warehouse) is a database:

- optimized for generating quick reports;

- where the data is not modified in real time;

- where the tables are denormalized (the information can be dupplicated in the same schema);

- which has a staging area with row information and an access area with prepared information (ready for reporting);

- generally bigger than 1 Tb of information;

- accessed by different tools for generating different reports;

- is used for strategic decision.

 

 

Attention:

 

A data mart is a repository of data gathered from operational data and other sources that is designed to serve a particular community of knowledge workers. In scope, the data may derive from an enterprise-wide database or data warehouse or be more specialized. The emphasis of a data mart is on meeting the specific demands of a particular group of knowledge users in terms of analysis, content or presentation.

 

 

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