The request
From Andrew Wallace, Head of Mobile
“I'm asking for budget to rebuild the app's checkout, and the CFO wants proof the app is growing, not just having a good Black Friday. For each month of 2025, app sales only: last year's sales, the monthly growth, and the year-to-date growth so far.”
Your goal
Step 1 of 3. Create a measure called Sales LY: Sales for the same period last year, with CALCULATE and SAMEPERIODLASTYEAR('Date'[Date]).
- Fill
[Sales LY]on every row of the visualnot done yet - The Total row right toonot done yet
Step 2 of 3. Keep Sales LY and add Sales YoY %: (Sales − Sales LY) ÷ Sales LY, with Sales LY in a variable and DIVIDE.
- Fill
[Sales YoY %]on every row of the visualnot done yet - The Total row right toonot done yet
Step 3 of 3. Keep both measures and add YTD Growth %: this year's year-to-date Sales against last year's year-to-date Sales at the same point, as a growth rate. Use TOTALYTD (or DATESYTD) for this year and DATESYTD(SAMEPERIODLASTYEAR('Date'[Date])) for last year, in variables, and DIVIDE.
- Fill
[YTD Growth %]on every row of the visualnot done yet - The Total row right toonot done yet
Step 1 · your measure
- Visual
- A matrix: rows = 'Date'[Month]; values = [Sales], [Sales LY]
- Slicers
- 'Date'[Year] = 2025orders[channel] = app
- Measures in the report
Sales = CALCULATE(SUM(order_items[line_total]), orders[status] = "completed")
Data pane: tables and columns
- order_items order_item_id, order_id, product_id, quantity, unit_price, discount_pct, line_total
- orders order_id, customer_id, order_date, status, channel, shipping_fee, coupon_code
- products product_id, name, category, subcategory, unit_price, unit_cost, launched_on, is_active
- customers customer_id, first_name, last_name, email, city, state, signup_date, segment, referral_source
- returns return_id, order_item_id, returned_on, reason, refund_amount
- Date Date, Year, Quarter, Month Number, Month, Year Month, Year Quarter, Day, Weekday Number, Weekday
Loading the editor…
Reference solution
| Month | Sales | Sales LY |
|---|---|---|
| Jan | $38,566 | |
| Feb | $46,574 | |
| Mar | $80,375 | |
| Apr | $91,823 | |
| May | $94,842 | |
| Jun | $97,194 | |
| Jul | $77,398 | |
| Aug | $71,746 | |
| Sep | $67,690 | |
| Oct | $80,288 | |
| Nov | $118,602 | |
| Dec | $130,426 | |
| Total | $995,524 |
Mote checks your result
Press Check. Mote fills in your answer and compares it with what the report needs.
Step 2 · your measure
- Visual
- A matrix: rows = 'Date'[Month]; values = [Sales], [Sales YoY %]
- Slicers
- 'Date'[Year] = 2025orders[channel] = app
- Measures in the report
Sales = CALCULATE(SUM(order_items[line_total]), orders[status] = "completed")
Data pane: tables and columns
- order_items order_item_id, order_id, product_id, quantity, unit_price, discount_pct, line_total
- orders order_id, customer_id, order_date, status, channel, shipping_fee, coupon_code
- products product_id, name, category, subcategory, unit_price, unit_cost, launched_on, is_active
- customers customer_id, first_name, last_name, email, city, state, signup_date, segment, referral_source
- returns return_id, order_item_id, returned_on, reason, refund_amount
- Date Date, Year, Quarter, Month Number, Month, Year Month, Year Quarter, Day, Weekday Number, Weekday
Loading the editor…
Reference solution
| Month | Sales | Sales YoY % |
|---|---|---|
| Jan | $38,566 | |
| Feb | $46,574 | |
| Mar | $80,375 | |
| Apr | $91,823 | |
| May | $94,842 | |
| Jun | $97,194 | |
| Jul | $77,398 | |
| Aug | $71,746 | |
| Sep | $67,690 | |
| Oct | $80,288 | |
| Nov | $118,602 | |
| Dec | $130,426 | |
| Total | $995,524 |
Mote checks your result
Press Check. Mote fills in your answer and compares it with what the report needs.
Step 3 · your measure
- Visual
- A matrix: rows = 'Date'[Month]; values = [Sales], [YTD Growth %]
- Slicers
- 'Date'[Year] = 2025orders[channel] = app
- Measures in the report
Sales = CALCULATE(SUM(order_items[line_total]), orders[status] = "completed")
Data pane: tables and columns
- order_items order_item_id, order_id, product_id, quantity, unit_price, discount_pct, line_total
- orders order_id, customer_id, order_date, status, channel, shipping_fee, coupon_code
- products product_id, name, category, subcategory, unit_price, unit_cost, launched_on, is_active
- customers customer_id, first_name, last_name, email, city, state, signup_date, segment, referral_source
- returns return_id, order_item_id, returned_on, reason, refund_amount
- Date Date, Year, Quarter, Month Number, Month, Year Month, Year Quarter, Day, Weekday Number, Weekday
Loading the editor…
Reference solution
| Month | Sales | YTD Growth % |
|---|---|---|
| Jan | $38,566 | |
| Feb | $46,574 | |
| Mar | $80,375 | |
| Apr | $91,823 | |
| May | $94,842 | |
| Jun | $97,194 | |
| Jul | $77,398 | |
| Aug | $71,746 | |
| Sep | $67,690 | |
| Oct | $80,288 | |
| Nov | $118,602 | |
| Dec | $130,426 | |
| Total | $995,524 |
Mote checks your result
Press Check. Mote fills in your answer and compares it with what the report needs.
What Andrew gets, and why
The lesson
Andrew needs a growth story that survives a skeptical CFO. That takes three columns: what last year looked like, how each month compares, and where the year stands so far. Each is one of this chapter’s patterns, and each builds on the one before.
What you are working in
This page runs a practice DAX engine built for this site. Each step evaluates your newest measure in the matrix (months on the rows, 2025 and the app channel from the slicers) and checks every cell. Keep earlier measures in the editor: later ones use them. In Power BI Desktop, create each with Home → New measure, format the two growth measures as percentages, and add the two slicers.
Step 1: last year, same period
Sales LY = CALCULATE([Sales], SAMEPERIODLASTYEAR('Date'[Date]))The calendar filters (the Month row, the 2025 slicer) are replaced by last year’s dates, because
the Date table is marked. The channel slicer is on orders, a different table, so it stays: the
measure compares app with app.
Step 2: monthly growth
Sales YoY % =
VAR ly = [Sales LY]
RETURN
DIVIDE([Sales] - ly, ly)The variable holds last year’s value once; DIVIDE protects the months where last year is blank.
Step 3: year-to-date growth
A single month can mislead: one strong promotion last year makes this year’s month look weak. The year-to-date comparison smooths that out. It needs two running totals, so two variables:
YTD Growth % =
VAR ytd = TOTALYTD([Sales], 'Date'[Date])
VAR ytdLY = CALCULATE([Sales], DATESYTD(SAMEPERIODLASTYEAR('Date'[Date])))
RETURN
DIVIDE(ytd - ytdLY, ytdLY)ytdLY nests the functions: shift the visible month back a year, then extend it to January 1.
Writing them as two separate CALCULATE filters would intersect 2025 dates with 2024 dates and
return a blank.
Reading the report
The monthly column has one red cell: November, −7.1%. Taken alone it would sink the budget request. The YTD column answers it: the app was ahead of 2024 at every point of the year and finished 53.1% up. Present the two side by side, monthly growth for where things changed, YTD growth for where the year stands, and the November dip becomes a footnote.
Common mistakes
- Putting the channel filter inside the measures. It works for this page but makes every measure app-only. Leave it to the slicer so the same measures serve web and marketplace.
- Growth on the Total row of the monthly column. It compares whole years; it is not an average of the twelve monthly rates.
- Hard-coded years.
'Date'[Year] = 2024instead of SAMEPERIODLASTYEAR breaks when the slicer moves to 2024.
Lantern lit!
Practised: sameperiodlastyearyoydatesytdtotalytdvar
- Solved
- No hints
- First run