Question

Why is my DAX measure displaying incorrect values when using time intelligence functions?

I’m working on a Power BI report using time intelligence functions like TOTALYTD, SAMEPERIODLASTYEAR, etc., but the DAX measures are returning incorrect values. The totals or comparisons don’t match expectations, and I suspect the issue lies in how my date table or DAX calculations are structured. What are the best practices for using time intelligence functions in Power BI, and how can I troubleshoot the incorrect values?

Answer 1

• There are some common issues and solutions concerning the incorrect results produced by DAX time intelligence computation methods such as TOTALYTD or SAMEPERIODLASTYEAR.
• First and foremost, check if your date table is properly set up. All measures or calculations that utilize time intelligence in Power BI require a date table distinct from all other tables that contain a complete range or set of dates across the period of analysis. Apart from that, this table should have all the relevant headers (like year, month, day, etc.) plus a key column that is complete without missing or repeated entries. It is also important that the data table is marked as a ‘Date Table’ in Power BI, which ensures the DAX functions call it for time-related calculations. Any omissions in the dates probably in your date dimension table or failure to mark a date dimension table may bring about wrong results at some point.
• Please also check the connections of your date table to other fact tables. In a perfect scenario, the date table should be connected to the main data table one to many with regard to the date column. Do not relate multiple fact table date fields to the date table, as this can be confusing while using DAX measures. In cases where various date-related computations are desired (like order date and ship date), design date tables in different aspects.
• Finally, check your DAX calculations and assess whether there is any possible wrong usage of time functions. For instance, functions such as SAMEPERIODLASTYEAR and TOTALYTD are best used with the uninterrupted range of dates and may return incorrect results when used on cut-over dates that are filtered or ranges that are not unbroken. In case you are applying some date range filters in the reports or running queries that involve certain date ranges, make sure targets in those two aspects are the same as those in your DAX equations. Most of the problems with incorrect time intelligence value inputs in Power BI can be solved by making appropriate arrangements for their date tables and their relationship to the date calculation functions.