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JimSales81
Frequent Visitor

Dax for 30 days before and 30 days after

Hello,

 

My company has a new pricing program.  Each customer can enter the program by signing a new contract (i.e. each customer's entry date will be different).  I want to normalize everything by creating a measure to show 30 days before and 30 days after contract signing date.  

 

I.e. if Customer A signed contract on 4/15, I want the forumla to identify each sale within 30 days before or after, calculate how many days from the contract signing date it is and plot that point on a line chart. 

 

 

What i'm hoping to get is:

if Customer A sold 10k on 4/17 that is +2 days from contact signing .  If they sold 3K on 4/10 that is -5

 

If customer B, whose contract date was 5/10 sold 30K on 5/12 it is also +2 days from contract signing.   If they sold 2k on 5/5 that is -5.  


When i plot the chart the orgin would be 0 and +2 would be 40K and -5 would be 5k.

 

Thanks for any help!

 

 

1 ACCEPTED SOLUTION
Jihwan_Kim
Super User
Super User

Hi,

I am not sure how your semantic model looks like, but I tried to create a sample pbix file like below.
One of ways to achieve this is to create a calculated column in the fact table.

Please check the below pictures and the attached pbix file.

 

 

Jihwan_Kim_1-1716865380238.pngJihwan_Kim_2-1716865394173.png

 

 

 

date_offset_by_entry_date_CC =
VAR _customer = sales_fact[customer]
VAR _entrydate =
    MAXX (
        FILTER ( customer_dimension, customer_dimension[customer] = _customer ),
        customer_dimension[entry_date]
    )
RETURN
    INT ( sales_fact[date] - _entrydate )

 

And then, create a measure with having the calculated column on the x-axis.

 

Sales expected result: = 
CALCULATE (
    SUM ( sales_fact[sales] ),
    FILTER (
        sales_fact,
        sales_fact[date_offset_by_entry_date_CC] >= -30
            && sales_fact[date_offset_by_entry_date_CC] <= 30
    )
)

 

Jihwan_Kim_0-1716865336344.png

 

If this post helps, then please consider accepting it as the solution to help other members find it faster, and give a big thumbs up.


Visit my LinkedIn page by clicking here.


Schedule a meeting with me to discuss further by clicking here.

View solution in original post

2 REPLIES 2
Jihwan_Kim
Super User
Super User

Hi,

I am not sure how your semantic model looks like, but I tried to create a sample pbix file like below.
One of ways to achieve this is to create a calculated column in the fact table.

Please check the below pictures and the attached pbix file.

 

 

Jihwan_Kim_1-1716865380238.pngJihwan_Kim_2-1716865394173.png

 

 

 

date_offset_by_entry_date_CC =
VAR _customer = sales_fact[customer]
VAR _entrydate =
    MAXX (
        FILTER ( customer_dimension, customer_dimension[customer] = _customer ),
        customer_dimension[entry_date]
    )
RETURN
    INT ( sales_fact[date] - _entrydate )

 

And then, create a measure with having the calculated column on the x-axis.

 

Sales expected result: = 
CALCULATE (
    SUM ( sales_fact[sales] ),
    FILTER (
        sales_fact,
        sales_fact[date_offset_by_entry_date_CC] >= -30
            && sales_fact[date_offset_by_entry_date_CC] <= 30
    )
)

 

Jihwan_Kim_0-1716865336344.png

 

If this post helps, then please consider accepting it as the solution to help other members find it faster, and give a big thumbs up.


Visit my LinkedIn page by clicking here.


Schedule a meeting with me to discuss further by clicking here.

vicky_
Super User
Super User

Good Ol SLQBI has a recent article that covers something very similar: https://www.sqlbi.com/articles/comparing-cumulative-values-for-events-in-different-periods/

In particlar, I would look at the Preparing the Model section and adapt that to suit your needs.

 

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