7 Conclusion

Data Viewing is an important subject whenever mass of data is involved in modeling. For this we use reporting, data browsing tools and data editing tools. When uniformed data are stored along several dimensions, then we may pack them into datacubes. These data are best viewed and edited through pivot-tables, the 2-dimensional representation of any datacubes.

This paper tries to give a unified theory on datacube and pivoting. It was shown that all data operations in OLAP can by reduced to slicing, dicing, sizing, and rising operations in a multidimensional datacube. The goal is to reduce all kind of proposed operations in OLAP to a few operations in manipulating datacubes. This gives also a new view in implementing OLAP tools. It is, furthermore, important to note that all aspects of data viewing of unified mass of data stored as datacubes can be accessed through pivot-tables. Pivot-tables are easy to understand (if implemented correctly) and easy to manipulate – at least from the point of view of the user. This paper shows that – given a datacube – a few operations and options determine a particular pivot-table. If the user understands these few operations, it is easy to use them. Unfortunately, Excel pivot-tables do not have these properties.