Reputation: 1948
I have a table in SSAS tabular mode that shows how individual pieces of products moved through different sections of a production line:
Product_ID, section_ID, Category_id (product category), time_in (when a product entered the section), time_out (when the product exited the section)
This is how the input table looks like:
I would like to write a measure in DAX that can show me the stock of each section and product category day-by-day as shown below by counting the number of distinct product ids which were in a particular section on that day.
I'm using SQL Server 2017 Analysis Services in Tabular Mode and Excel Pivot Table for representation.
Upvotes: 0
Views: 279
Reputation: 40204
Create a new table that has all of the dates that you want to use for your columns. Here's one possibility:
Dates = CALENDAR(MIN(ProductInOut[time_in]), MAX(ProductInOut[time_out]))
Now create a measure that counts rows in your input table satisfying a condition.
ProductCount =
VAR DateColumn = MAX(Dates[Date])
RETURN COUNTROWS(FILTER(ProductInOut,
ProductInOut[time_in] <= DateColumn &&
ProductInOut[time_out] >= DateColumn)) + 0
Now you should be able to set up a pivot table with Category_id
on the rows and Dates[Date]
on the columns and ProductCount
as the values.
Upvotes: 1