In cases where your dataset is not perfectly a time series, particularly with regard to the time intelligence functions in Power BI, a solution exists whereby you create a new date table consisting of a date range. This is important since functions written using DAX, such as TOTALYTD, SAMEPERIODLASTYEAR, etc., would work correctly without the missing dates.
Here is the simplest solution you could use:
There is a Date Table: In Power BI, click “Modeling” > “New Table” and write a formula that will create a continuous list of dates starting from today, such as:
DateTable = CALENDAR (DATE(2020, 1, 1), DATE(2023, 12, 31))
Modify the beginning and finishing dates in accordance with the range required for your task.
Mark as Date Table: This involves selecting the recently created DateTable, proceeding to “Modeling” > “Mark as Date Table,” and setting the main date column. This step is very important since it informs Power BI where the main dates operations will be drawn from.
Establish Relationship Between Date Table and Fact Table: Connect the DateTable with the date dimension, in this case, the primary data (fact) table. A one-to-many marriage is used, with the DateTable being the ‘one’ side.
Use Date Table in Time Intelligence Functions: Now start using columns from your DateTable in DAX functions. Since it is a continuous date table, it will not be a problem as the time intelligence functions like TOTALYTD and SAMEPERIODLASTYEAR will function properly, even if there are missing dates in the original dataset.
By adding a specific date table in the model, the issue of missing data can be addressed, and time-based analysis can be confidently carried out in Power BI.
