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In this pattern, you compare the two columns that define the relationship between the tables; you will adapt this comparison to the columns used in your data model.
Thanks to this check, you avoid the propagation of the last value in periods that are later than the last transactions in your data.
You apply the filter to the Date column of the Date table, which must be marked as a Date table in the data model.
You can use the Cumulative Total pattern whenever you want to show the total of a measure up to a certain date, considering all the previous operations (even those earlier than the current selection of dates).
Most transactional systems already have a built-in calculation for these accounts that saves the updated cumulative value to the accounts involved in each transaction.
You can use the Cumulative Total pattern to rebuild the historical or predicted behavior at any given granularity.
You can use or adapt the Cumulative Quantity pattern to this purpose.
You apply the Cumulative Total pattern to models that have a table marked as a Date table in the data model.Figure 4 shows a data model where the relationship between the Transactions table and the Date table is defined using an integer column (Date Key).The Date table is marked as a Date table in the data model by use of the Date column.At any given date, the Cumulative Quantity measure displays the Sum of Quantity for all the transactions made on a date that is less than or equal to the selected date.For example, the Cumulative Quantity of February 2013 corresponds to the sum of December 2012, January 2013, and February 2013.In Figure 1, the Transactions table has a relationship with the Date table.Tags: Adult Dating, affair dating, sex dating