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Hi
I have attached a table as sample data if you can help me please. I'd like to have YOY% growth on both Sales amount and QTY. Data is from 2019 to 2022. I have applied the Pivot command on Year column, it only gives me YOY% on one measure (e.g. Sales Amount). How can I have both Sales Amount and QTY YOY% growth in one table (or other visuals later)? I would need to keep the other info in other columns to slice the data later once YOY% is calculated.
My 2nd question following above: I'd need to have it as YTD amount, e.g by the end of November to compare the current year vs. the previous years (2022 vs. 2021 in particular).
My 3rd question following above: Is it very difficult/impossible to add MOM% as well in the same run as YOY% above?
Thank you for your help.
Solved! Go to Solution.
See attached for YoY%. Your sample data is not good enough for MoM% but you can use the same approach. Instead of DATEADD(xxx,-12, MONTH) use DATEADD(xxx,-1,MONTH)
please provide sample data in usable format.
Hi Ibendlin
I got this and visualised YOY% and MOM%. Thank you
Thank you for your time and help. I'll check my dataset for MOM as well.
Cheers
Hi Ibendlin. Thank you for your reply. I am new here and may need some guidance, please. I searched how I can add a sample dataset in Power BI or Excel format here and it seems only superusers can. I am not sure if pasting a smaller sample dataset in a table format as per above would help. Thank you
Item No | Item Desc. | Model Group | IG | GP | Make | Location | Date (Year) | Date (Month) | Date (Date) | Vendor | Amount | QTY |
6BE06984HJ6BG | Pad | White | B | F2 | Du | Sydney | 2019 | December | 5/12/2019 | 2A012A2A | 117.26 | 21 |
6BE06984HJ6BG | Pad | White | B | F2 | Du | Sydney | 2019 | December | 12/12/2019 | 2A012A2A | -58.59 | -10 |
6B306986BHJ6B | Pad | Blue | B | P5 | Du | Sydney | 2020 | January | 28/01/2020 | 2A012A2A | 77.64 | 14 |
6B306986BHJ6B | Pad | Blue | B | P5 | Du | Sydney | 2020 | February | 26/02/2020 | 2A012A2A | 68.67 | 12 |
6B306986BHJ6BB | Pad | Blue | B | 21 - G4 | Du | Sydney | 2021 | August | 30/08/2021 | 2A012A2A | 180.92 | 31 |
6B306984HJ6BG | Pad | Blue | B | 21 - G4 | Du | Sydney | 2019 | March | 13/03/2019 | 2A012A2A | 35.42 | 7 |
6BP5 | Pad | Blue | B | P5 | Du | Sydney | 2019 | January | 30/01/2019 | 2A012A2A | 69.95 | 13 |
6BP5 | Pad | Blue | B | P5 | Du | Sydney | 2019 | February | 26/02/2019 | 2A012A2A | 70.76 | 13 |
6BP5 | Pad | Blue | B | P5 | Du | Sydney | 2019 | March | 6/03/2019 | 2A012A2A | 70.76 | 13 |
6BP5 | Pad | Blue | B | P5 | Du | Sydney | 2019 | March | 18/03/2019 | 2A012A2A | 70.76 | 13 |
6BP5 | Pad | Blue | B | P5 | Du | Sydney | 2019 | December | 10/12/2019 | 2A012A2A | 70.76 | 13 |
6BP5 | Pad | Blue | B | P5 | Du | Sydney | 2020 | December | 2/12/2020 | 2A012A2A | 70.29 | 13 |
6BP5 | Pad | Blue | B | P5 | Du | Sydney | 2022 | August | 10/08/2022 | 2A012A2A | 78.69 | 14 |
6BJ066BHJ306B43 | Mouse | Purple | A | 40 - B2/Du/T2/K7 | Du | Sydney | 2019 | January | 21/01/2019 | 2A012A2A | 123.48 | 21 |
6BJ066BHJ306B43 | Mouse | Purple | A | 40 - B2/Du/T2/K7 | Du | Sydney | 2019 | January | 31/01/2019 | 2A012A2A | 123.48 | 21 |
6BJ066BHJ306B43 | Mouse | Purple | A | 40 - B2/Du/T2/K7 | Du | Sydney | 2019 | February | 4/02/2019 | 2A012A2A | 55.47 | 21 |
6BJ066BHJ306B43 | Mouse | Purple | A | 40 - B2/Du/T2/K7 | Du | Sydney | 2019 | March | 4/03/2019 | 2A012A2A | 56.10 | 22 |
6BJ066BHJ306B43 | Mouse | Purple | A | 40 - B2/Du/T2/K7 | Du | Sydney | 2019 | March | 7/03/2019 | 2A012A2A | 56.10 | 22 |
6BJ066BHJ306B43 | Mouse | Purple | A | 40 - B2/Du/T2/K7 | Du | Sydney | 2019 | March | 25/03/2019 | 2A012A2A | 56.10 | 22 |
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