Data modeling (calculation between tables)

Dear All
I have two data tables:
Table 1.
week number
calendar day
01
02.01.2014
01
03.01.2014
01
04.01.2014
01
05.01.2014
02
06.01.2014
02
07.01.2014
02
08.01.2014
02
09.01.2014
02
10.01.2014
02
11.01.2014
02
12.01.2014
03
13.01.2014
Table 2.
Brand
Start period
End Period
Ad size (cm²)
A
02.01.2014
13.01.2014
24
B
05.01.2014
10.01.2014
41
What I need is to receive pivot table looking like this:
week number
AVG (Ad size (cm²))
01
02
03
How to calculate average of Ad size (cm²) per week which would be weighted by days?
I have done this manualy:
week number
calendar day
Brand A
Ad size (cm²)
Brand B
Ad size (cm²)
AVG (Ad size (cm²))
01
2014-01-02
24
01
2014-01-03
24
01
2014-01-04
24
01
2014-01-05
24
41
01
27,4
02
2014-01-06
24
41
02
2014-01-07
24
41
02
2014-01-08
24
41
02
2014-01-09
24
41
02
2014-01-10
24
41
02
2014-01-11
24
02
2014-01-12
24
02
31,1
03
2014-01-13
24
03
24
And received results like this:
week number
AVG (Ad size (cm²))
01
27,4
02
31,1
03
24,0
But it is not a solution. I need this to be done automaticly.
How to start? Write a maesure? or Add calculated column?
How the syntax should look like?
Thanks for ideas
G.

Mike
Thank you very much.
The measure above works, but it is not optimize in this case.
My goal is to calculate measure separately for each week and year.
so I have added new columns to both Table 1. (YEAR and YEAR&WEEK) and Table 2 (YEAR)
Table 1.
week number
calendar day
YEAR
YEAR&WEEK
1
01.01.2012
2012
2012 1
2
02.01.2012
2012
2012 2
2
03.01.2012
2012
2012 2
2
04.01.2012
2012
2012 2
2
05.01.2012
2012
2012 2
2
06.01.2012
2012
2012 2
2
07.01.2012
2012
2012 2
2
08.01.2012
2012
2012 2
3
09.01.2012
2012
2012 3
3
10.01.2012
2012
2012 3
3
11.01.2012
2012
2012 3
3
12.01.2012
2012
2012 3
3
13.01.2012
2012
2012 3
3
14.01.2012
2012
2012 3
53
31.12.2014
2014
2014 53
Table 2.
Brand
Start period
End Period
Ad size (cm²)
YEAR
Acme
27.05.2013
01.06.2013
15
2013
Acme
16.09.2013
21.09.2013
18
2013
Acme
04.11.2013
09.11.2013
17
2013
Acme
02.09.2013
07.09.2013
37
2013
Acme
13.05.2013
18.05.2013
19
2013
Acme
06.01.2014
11.01.2014
19
2014
Adidas
25.04.2013
15.05.2013
36
2013
Adidas
25.04.2013
15.05.2013
37
2013
Adidas
25.04.2013
15.05.2013
37
2013
Adidas
25.04.2013
15.05.2013
37
2013
Akai
09.01.2013
15.01.2013
44
2013
Akg
16.10.2013
03.11.2013
54
2013
Asus
17.12.2012
31.12.2012
51
2012
Audiola
01.12.2013
31.12.2013
240
2013
Beats By Dr. Dre.
11.09.2013
24.09.2013
57
2013
Beats By Dr. Dre.
11.09.2013
24.09.2013
57
2013
Beats By Dr. Dre.
04.12.2013
09.12.2013
31
2013
Beats By Dr. Dre.
24.04.2013
15.05.2013
155
2013
Beats By Dr. Dre.
25.04.2013
15.05.2013
173
2013
Beats By Dr. Dre.
25.04.2013
15.05.2013
54
2013
I tried to modify this measure :
=AVERAGEX(
            FILTER(
                     CROSSJOIN(Table1, Table2),
                     Table1[Calendar Day]>=Table2[Start Period]
                     Table1[Calendar Day]<=Table2[End Period]
                      Table1[YEAR]=Tabl2[YEAR]
           Table2[Ad size
(cm²)]
or:
=AVERAGEX(
            FILTER(
                     CROSSJOIN(Table1, Table2),
                     Table1[Calendar Day]>=Table2[Start Period]
                     Table1[Calendar Day]<=Table2[End Period]
VALUES(Table1[YEAR])=VALUES(Tabl2[YEAR])
           Table2[Ad size
(cm²)]
but in both cases the following error occured:
"the function averagex takes an argument that evaluates to numbers and dates and cannot work with values of type Boolean"
Data types of YEAR are in both tables formated as Whole Number. With Text format the error also occcurs. I cannot change Data types to Dates becouse get another error: "Data type conversion failed"
How the proper measure should look like?
What if I would like to add to this measure new Tables of a same structure as Table 2. Let us called it Table 2a and Table 2b. These tables will store data from other markets. How the measure will look like in this case?
The goal is to calculate this measure for all markes together and also for each one separately. For second option I will create additional related table of markets.
G

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