DATESYTD (or any Time Intelligent Function) Working Off Other Data Besides Date in the Pivot Table

I am working on a project where I need to count the number of events from the start of the year to the end for each year in the data with each event counting the current event and any previous events sequentially. My results should look like the following:
MarketNameDate
MarketCount
2012-09-11|Kansas City
1
2012-09-18|Denver
2
2012-09-25|Chicago
3
2012-10-02|Seattle
4
2012-10-09|Phoenix
5
2012-10-16|Tampa
6
2012-10-23|Norfolk
7
2012-10-30|Alexandria
8
2012-11-06|San Jose
9
2012-11-27|Dallas
10
2012-12-04|Fort Lauderdale
11
2013-01-15|Los Angeles
1
2013-01-22|Orange County
2
My formula is as follows :=calculate(distinctcount(Event_Table[MarketNameDate]),datesytd(dates_dimensions[date_value]),all(dates_dimensions)). This formula works correctly when I am using the Date_Dim table to drive the analysis in the Row Label or
Column Label in my Pivot Table. My events table is connected directly to Date_Dim table and I would like to use the [MarketNameDate] field instead.
I need to get a rolling count of the number of markets through the year, but roll up on [MarketNameDate] instead of anything out of Date_Dim. Is this possible or do the Time Intelligence functions require you to only use Date_Dim columns as Row Label
or Column Label in my Pivot Table.
I would also be happy to have an alternative way of solving the problem if there is a way to do it.
Here is an approximation of the data I am using.
Seminar_Events
Event_Type
Market
MarketNameDate
MarketMinDate
Preview
Kansas City
2012-09-11|Kansas City
9/11/2012 0:00
Workshop
Kansas City
2012-09-11|Kansas City
9/11/2012 0:00
Preview
Denver
2012-09-18|Denver
9/18/2012 0:00
Workshop
Denver
2012-09-18|Denver
9/18/2012 0:00
Preview
Chicago
2012-09-25|Chicago
9/25/2012 0:00
Workshop
Chicago
2012-09-25|Chicago
9/25/2012 0:00
Preview
Seattle
2012-10-02|Seattle
10/2/2012 0:00
Workshop
Seattle
2012-10-02|Seattle
10/2/2012 0:00
Preview
Phoenix
2012-10-09|Phoenix
10/9/2012 0:00
Workshop
Phoenix
2012-10-09|Phoenix
10/9/2012 0:00
Preview
Tampa
2012-10-16|Tampa
10/16/2012 0:00
Workshop
Tampa
2012-10-16|Tampa
10/16/2012 0:00
Preview
Norfolk
2012-10-23|Norfolk
10/23/2012 0:00
Workshop
Norfolk
2012-10-23|Norfolk
10/23/2012 0:00
Preview
Alexandria
2012-10-30|Alexandria
10/30/2012 0:00
Workshop
Alexandria
2012-10-30|Alexandria
10/30/2012 0:00
Preview
San Jose
2012-11-06|San Jose
11/6/2012 0:00
Workshop
San Jose
2012-11-06|San Jose
11/6/2012 0:00
Preview
Dallas
2012-11-27|Dallas
11/27/2012 0:00
Workshop
Dallas
2012-11-27|Dallas
11/27/2012 0:00
Preview
Fort Lauderdale
2012-12-04|Fort Lauderdale
12/4/2012 0:00
Workshop
Fort Lauderdale
2012-12-04|Fort Lauderdale
12/4/2012 0:00
Preview
Los Angeles
2013-01-15|Los Angeles
1/15/2013 0:00
Workshop
Los Angeles
2013-01-15|Los Angeles
1/15/2013 0:00
Preview
Orange County
2013-01-22|Orange County
1/22/2013 0:00
Date_Dimensions
date_value
1/1/2012 0:00
1/2/2012 0:00
1/3/2012 0:00
1/4/2012 0:00
1/5/2012 0:00
ETC
There is a relationship created between Date_Dimensions[Date_Value] and Seminar_Events[MarketDateName]
Any help would be very much appreciated.
Kind Regards,
John

If you want a running count on MarketNameDate, you need to create a numeric ranking of that column in a new calculated column in your Events table.
Something like:
Rank = RANKX(ALL(Events), [MarketNameDate], ,1)
You should also add a year calculated column in that table:
Year = YEAR([MarketMinDate])
Once those are in place, this measure should work for you:
MarketCount:=
CALCULATE(
DISTINCTCOUNT(
Events[MarketNameDate]
FILTER(
ALL(Events),
Events[Rank] <= MAX(Events[Rank])
&& Events[Year] = MAX(Events[Year])
Mike, can you check out this thread?
http://social.msdn.microsoft.com/Forums/sqlserver/en-US/a2e22d61-7c32-43f2-900e-d9d6325fa26d/needed-more-answerers?forum=sqlkjpowerpivotforexcel
Thanks!
Ed Price, Power BI & SQL Server Customer Program Manager (Blog,
Small Basic,
Wiki Ninjas,
Wiki)
Answer an interesting question?
Create a wiki article about it!

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DATESYTD (or any Time Intelligent Function) Working Off Other Data Besides Date in the Pivot Table

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