By Sivakumar Harinath
ISBN-10: 0470247983
ISBN-13: 9780470247983
- When used with the MDX question language, SQL Server research prone permits builders to construct full-scale database functions to aid such enterprise capabilities as budgeting, forecasting, and marketplace analysis.
- Shows readers tips on how to construct info warehouses and multi-dimensional databases, question databases, and use research prone and different elements of SQL Server to supply end-to-end solutions
- Revised, up to date, and greater, the publication discusses new positive aspects similar to more advantageous integration with place of work and Excel 2007; question functionality improvements; advancements to aggregation dressmaker, size fashion designer, dice and size wizards, and phone writeback; extensibility and personalization; info mining; and more
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Extra info for Professional Microsoft SQL Server Analysis Services 2008 with MDX
Sample text
This is the default and recommended storage mode for Analysis Services databases because you get better query performance as compared to the other storage types. The key advantages of this storage mode is fast data retrieval while analyzing sections of data and therefore provides good query performance and the ability to handle complex calculations. Two potential disadvantages of MOLAP mode are storage needed for large databases and the inability to see new data entering your data warehouse. ROLAP is the storage mode in which the data is left in the relational database.
During the time the cache is being built, results are retrieved from the relational database. UDM helps in providing real-time data access with the speed of an OLAP database due to the MOLAP cache. This feature is called proactive caching. You learn more about proactive caching in Chapter 21. ❑ Rich metadata, ease of use for exploration, and navigation of data: UDM provides a consolidated view of the underlying data sources with the richness of metadata provided by the OLAP world. Due to rich metadata supported by OLAP, end users are able to exploit this metadata to navigate and explore data in support of making business decisions.
If the queries to Analysis Services request aggregated data, they are retrieved from the summary data stored on the Analysis Services instance and they would be faster than data being retrieved from the relational backend. If the queries request detailed data, appropriate queries are sent to the relational backend and these queries can take a long time based on the relational backend. If you choose the data and/or aggregated data to be stored in the optimized MOLAP format, you get better query performance than the ROLAP format, where data is being retrieved from the relational database.
Professional Microsoft SQL Server Analysis Services 2008 with MDX by Sivakumar Harinath
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