This answer has been deleted. This answer has been undeleted. Each of these requests has its own request ID, which is included in the fact table in the package dimension. This makes it possible to pay particular attention to individual requests. One advantage of the request ID concept is that you can subsequently delete complete requests from the InfoCube.
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Infocube Compression I was dealing with the tab "compression" while managing the infocube, was able to compress the infocube and send in the E- table but was unable to find the concrete answer on the following isssues: 1. What is the exact scenario when we use compression? What actually happens in the practical scenario when we do compression?
What are the advantages of compressing a infocube? What are the disadvantages of compressing a infocube? Compression creates a new cube that has consolidated and summed duplicate information.
When you compress, BW does a group by on dimensions and a sum on measures Compressed infocubes require less storage space and are faster for retrieval of information. Once a cube is compressed, you cannot alter the information in it.
This can be a big problem if there is an error in some of the data that has been compressed. I understand the advantage to compressed the infocube is the performance. But I have a doubt. If I compressed one or more request ID of my infocube the data it will continue to appear in my reports Analyzer? The data will always be there in the Infocube. Compression yeap its for performance.
But before doing this compression you should keep in mind one thing very carefully. These two things are very important when you go for compression.
what is difference betwwen aggregates and compression in bi 7.0.
It aggregates records with equal keys from different requests. Refer Fig 1. Advantages: For DBMS supporting range partitioning, the E fact table is optimized for reporting with respect to database partitioning and the F fact table is optimized for data load and deletion. Compression prevents the F-table which is partitioned by request ID from containing too many partitions.
InfoCube Compression in SAP BI