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# Help In Data Modelling Semi Additive Measures

## Help In Data Modelling Semi Additive Measures

(OP)
I Need some Help In Datamodelling few of the Non Additive Measures.

Requirement is that I have some reports which compares the Golas with the Actual Booking amount at various levels of geography hirearchy. One example is Terriotry-->Region-->Area-->BU.Quota Amount changes quarter over quarter and the Region level data is different from the sum of the Territory Quota levels.

Could you please let me know how best this can be modelled.

Sample Data

Territory   Period  Quota
T1-->Q1-->$30M T2-->Q1-->$40M

Region Period  Quota

R1--->Q1--->\$70M

Required:

Region Quota  Booking Amount  Difference

### RE: Help In Data Modelling Semi Additive Measures

Is your sample really in line with your described case? you say that the Region level data is different from the sum of the territory quota levels.
Your sample data shows that the region data is the sum of the region data.

Can you give a more detailed description of the non-additive measures.

One way I have solved the problem of non-additive (and semi-additive) facts before is the use of pre-calculated aggregates.

### RE: Help In Data Modelling Semi Additive Measures

(OP)

My Meaning of Non Additive Measures is

a) As described above Region Level Quota may or may not be equal to sum of lowerlevel quotas (Territory).
b) Like Wise Quota will change quarter over quarter.
c) Analysis of Quota Comparison with Actuals need to be done at different levels in different hirerachies.
d) My Transactional data is available at the day level

It should have been some thing other than 70M.

### RE: Help In Data Modelling Semi Additive Measures

So, you have a really semi-additive fact. The quota are additive  over some dimensions, but not over other (like the hierarchy and (possibly) time).

What I have done is to handle this, is to create an aggregate fact-table, with the correct aggregates (in this case Quota).

So you have a fact table:
Territory - Quarter - Quota budget - other dimensions
T1          Q1        100
T2          Q1        140
T3          Q1        130
T1          Q2        120
T2          Q2        100
T3          Q2        155
...

And you build a aggregate fact table
Region  - Quarter - Quota budget - other dimensions
R1        Q1        175
R2        Q1        200
R1        Q2        180
R2        Q2        190
...

You then have to build an additional piece of ETL software to correctly fill the aggregate.

Hope this helps a bit.

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