Supporting Compression and Accuracy in Multidimensional OLAP Data Cubes

In this talk, we will present some techniques for 
supporting compression and accuracy in multidimensional OLAP data cubes. The 
proposed techniques can be efficiently used in Quality-of-Answer-based OLAP 
tools, where OLAP users/applications and Data Warehouse servers are allowed to 
mediate on the compression and accuracy of (approximate) answers. Two techniques 
are presented: LCS-Hist (EDBT’09), which is able to deal with high-dimensional 
data cubes, and D-Syn (SSDBM’06), which exploits an analytical interpretation of 
data cubes for making the intrinsic data cube compression more flexible.