Sorry no, not really.
Most of the business world use like for like calculations in doing YoY variances. Like for Like means you only include products/stores (depending what you are comparing) that appearred in both years. Any data from new stores or old stores is disregarded.
In excel/sql this task is relatively simple. You essentially lookup/inner join between 2 datasets to only pull information applicable in both.
I have a long winded way of doing it by creating 2 calculated fields per variance - 1 to determine if the product/store was available/open the previous year and another to determine what the last year value was if it was available/open. Frankly it's disappointing and I might as well add the value columns myself in SQL, but I thought I wouldn't have to duplicate data in Power Bi.
Also I work to a 4-4-5 calendar which is standard across the UK for retailers. This means I can't apply a MoM comparison directly. I have apply weekly averages and use a measure. This is ok but as the data is no longer at row level, the calculation can only be use din limited ways.
