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Data warehouses are designed to access large groups of related records.
Data marts improve end-user response time by allowing users to have access to the specific type of data they need to view most often by providing the data in a way that supports the collective view of a group of users.
The developer can now apply profile rules to the ADDR2 column based on the business rules provided.
Applying profiling rules allows the data steward to identify possible inconsistencies in the data and potentially correct the data in the source system.
This enables each department to isolate the use, manipulation and development of their data.
In other deployments where conformed dimensions are used, this business unit ownership will not hold true for shared dimensions like customer, product, etc.
One other underestimated strength that you are eluding, also important for agile BI scenarios, is the openness to third party BI platform/tools, including MS Sharepoint/MS BI, but also in memory data discovery platforms like Qliktech to empower lines of business with prototyping or self service scenarios.
Regarding the capabilities with data volume, my feeling is that, although BW would struggle with multi-terabyte warehouse, it can handle reasonable data volume (by that, I mean, not high end, but upper middle end rather that low end) : many BI surveys have shown that current BW customers handle, in average, bigger data volumes than the users of most other BI platforms.
Organizations build data warehouses and data marts because the information in the database is not organized in a way that makes it readily accessible, requiring queries that are too complicated or resource-consuming.
While transactional databases are designed to be updated, data warehouses or marts are read only.
after you are done selecting the package, report studio will validate your report specs based on the new package.Tags: Adult Dating, affair dating, sex dating