A More Complex Example

The flattened dataset from the section “Cube and Dataset Example.” looks like this:

[Quarters]. [MEMBER_ CAPTION]	[Months]. [MEMBER_ CAPTION]	[Venkatrao]. [The World]. [North America]. [USA]. [USA_North]. [Seattle]	[Venkatrao]. [The World]. [North America]. [USA]. [USA_North]. [Boston]	[Venkatrao]. [The World]. [North America]. [USA]. [USA_South]
Qtr1	Jan	00	10	20
Qtr1	Feb	01	11	21
Qtr1	Mar	02	12	22
Qtr2	NULL	03	13	23
Qtr3	NULL	04	14	24
Qtr4	Oct	05	15	25
Qtr4	Nov	06	16	26
Qtr4	Dec	07	17	27

(This is the same table continued.)

[Venkatrao]. [The World]. [Asia]. [Japan]	[Netz]. [The World]. [North America]. [USA]. [USA_North]. [Seattle]	[Netz]. [The World]. [North America]. [USA]. [USA_North]. [Boston]	[Netz]. [The World]. [North America]. [USA]. [USA_South]	[Netz]. [The World]. [Asia]. [Japan]
30	40	50	60	70
31	41	51	61	71
32	42	52	62	72
33	43	53	63	73
34	44	54	64	74
35	45	55	65	75
36	46	56	66	76
37	47	57	67	77

Note In this example, it is assumed that members from the Geography dimension need to be fully qualified to ensure uniqueness, while the members from all other dimensions do not.