You are a database developer and you have about two years experience in creating business intelligence (BI) solutions by using SQL Server2008.
Now you are employed in a company which is named NaproStar and work as the technical support for the company which uses SQL Server2008.
To meet the business development, you create a SQL Server 2008 Analysis Server (SSAS) solution with a measure group contained.
The measure group named Meatruth has a single partition. Now you are asked to not only make sure you have all aggregations that are part of the measure group stored in a multidimensional format, but also make sure the queries that use the measure group always refer to the newest edition of the source detail data. So what action should you perform to achieve that goal?
A.
You should set the ProactiveCaching property of the partition to scheduled multidimensional online analytical processing (MOLAP).
B.
You should set the ProactiveCaching property of the partition to real-time multidimensional online analytical processing (MOLAP)
C.
You should set the ProactiveCaching property of the partition to real-time hybrid online analytical processing (HOLAP).
D.
You should set the ProactiveCaching property of the partition to real-time relational online analytical processing (ROLAP)
E.
You should set the ProactiveCaching property of the partition to automatic multidimensional online analytical processing (MOLAP).
Explanation:
HYBRID OLAP
As its name suggests, HOLAP is a hybrid between MOLAP and ROLAP. In HOLAP, the cube data remains in the relational store, but the aggregations are stored on the SSAS server.
HOLAP is the most effi cient mode in terms of disk space because detail-level data is not duplicated, as it is with MOLAP, and HOLAP requires less space to store aggregations than ROLAP does.
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EXAM TIP
Choose the HOLAP storage mode if you want to store cube aggregations on the SSAS server but keep the fact data in the source database.
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In terms of query performance, HOLAP scores in the middle. If the query can be satisfi ed entirely by existing aggregations, HOLAP performs as well as MOLAP. But if it cannot be satisfied, the query is sent to the relational database, and performance suffers. In terms of processing times, HOLAP cubes might be processed faster than either MOLAP or ROLAP cubes because data is read only once to create aggregations. However, because SSAS has an efficient storage architecture, in real life MOLAP and HOLAP should give you comparable processing times, so it is best to consider HOLAP only for large historical partitions that are queried infrequently.